CN106845325B - A kind of information detecting method and device - Google Patents

A kind of information detecting method and device Download PDF

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Publication number
CN106845325B
CN106845325B CN201510885680.4A CN201510885680A CN106845325B CN 106845325 B CN106845325 B CN 106845325B CN 201510885680 A CN201510885680 A CN 201510885680A CN 106845325 B CN106845325 B CN 106845325B
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region
personage
video frame
target video
suspicious
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CN106845325A (en
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余倩
张富平
黄洋文
戴虎
邝宏武
朱江
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Hangzhou Hikvision Digital Technology Co Ltd
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Hangzhou Hikvision Digital Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
    • G06V20/42—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items of sport video content
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/46—Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Computational Linguistics (AREA)
  • Software Systems (AREA)
  • Image Analysis (AREA)

Abstract

The embodiment of the present application discloses a kind of information detecting method and device, is related to technical field of image processing, wherein the above method includes: the personage detected in target video frame；Obtain character positions of the detected personage in reference frame, wherein the reference frame are as follows: the acquisition moment is located at the preset quantity video frame before the acquisition moment of the target video frame；According to preset Region detection algorithms, the suspicious region in the target video frame is detected；According to the character positions in detected personage and the reference frame, determine whether the suspicious region of the target video frame is region there are abnormal conditions.Infomation detection is carried out using scheme provided by the embodiments of the present application, the region in video frame there are abnormal conditions can be effectively detected, alleviate the operating pressure of staff.

Description

A kind of information detecting method and device
Technical field
This application involves technical field of image processing, in particular to a kind of information detecting method and device.
Background technique
With social progress and economic development, the business in each city is more and more flourishing, shop along street cumulative year after year.Through Battalion person is often managed stand and is moved out of retail shop to outside retail shop to improve the turnover.Although in this way for operator with Carried out benefit, but be easy to cause traffic jam, influenced city appearance, for this purpose, supervision of law enforcement personnel need to ceaselessly go on patrol with Reduce the generation of such case.
Although operator can be reduced in such a way that law enfrocement official goes on patrol to move stand to outside retail shop out of retail shop Phenomenon, but with the development of economy, retail shop is more and more, and the operating pressure of law enfrocement official is also increasing.
Summary of the invention
The embodiment of the present application discloses a kind of information detecting method and device, and to detect, there are abnormal conditions in video frame Region mitigates the operating pressure of staff.
In order to achieve the above objectives, the embodiment of the present application discloses a kind of information detecting method, which comprises
Detect the personage in target video frame；
Obtain character positions of the detected personage in reference frame, wherein the reference frame are as follows: the acquisition moment is located at Preset quantity video frame before the acquisition moment of the target video frame；
According to preset Region detection algorithms, the suspicious region in the target video frame is detected；
According to the character positions in detected personage and the reference frame, the suspicious of the target video frame is determined Whether region is region there are abnormal conditions.
In a kind of specific implementation of the application, in the personage according to detected by and the reference frame Character positions determine whether the suspicious region of the target video frame is region there are abnormal conditions, comprising:
Obtain character positions of the detected personage in the target video frame；
According to the character positions in the character positions and the reference frame in the target video frame, determine detected Suspicious figure in personage；
Determine the suspicious region in the reference frame；
Obtain region corresponding with the suspicious region of the target video frame in the suspicious region of the reference frame；
Calculated in the target video frame between the suspicious figure and the suspicious region of the target video frame away from From, and the distance between the suspicious figure and region obtained are calculated in the reference frame；
According to calculated distance, determine whether the suspicious region of the target video frame is area there are abnormal conditions Domain.
In a kind of specific implementation of the application, character positions according in the target video frame and described Character positions in reference frame determine the suspicious figure in detected personage, comprising:
Judge whether to meet expression formula one,
Wherein, the expression formula one are as follows:
meand> TmAnd vard< Tv1,
meandIndicate the mean value of the mean deviation distance of detected each personage, vardIt is each detected by indicating The variance of the mean deviation distance of personage, TmIndicate preset mean value threshold value, Tv1It indicates preset first variance threshold value, is detected The mean deviation distance of any personage i out indicates that the personage i is acquired in the target video frame and the reference frame The average value of moving distance between moment adjacent two frames；
If not satisfied, judge whether to meet expression formula two,
Wherein, the expression formula two are as follows:
varp< Tv2And vard< Tv3,
varpIndicate the variance of the character positions in the target video frame, Tv2Indicate preset second variance threshold value, Tv3 Indicate preset third variance threshold values；
If not satisfied, mobile slow personage is determined from detected personage according to expression formula three, and according to expression formula Four determine suspicious figure from the slow personage of the movement,
Wherein, the expression formula three are as follows:
frmd> Tcnt1And distbias< Tdist1,
frmdAny personage j in personage detected by indicating goes out in the target video frame and the reference frame Existing number, distbiasIndicate the mean deviation distance of the personage j, Tdist1Indicate preset first offset distance threshold value, Tcnt1Indicate preset first amount threshold；
The expression formula four are as follows:
distrela< Tdist2And frms> Tcnt2,
distrelaIndicate position and the pos of the slow personage k of any movementaverThe distance between, posaverIndicate each shifting The history deflection for moving slow personage most locates position pos slowlyparLocation mean value, posparIndicate the slow personage k of any movement The position in video frame f is acquired, the personage k is moved to the moving distance of the video frame f from the former frame of the video frame f Are as follows: the minimum value of moving distance of the personage k between acquisition moment adjacent two video frames acquired, frmsIndicate institute State the number that personage k is confirmed as slowly mobile personage in the video frame acquired, Tdist2Indicate preset second offset distance From threshold value, Tcnt2Indicate preset second amount threshold.
It is described according to preset Region detection algorithms in a kind of specific implementation of the application, detect the target Suspicious region in video frame, comprising:
According to preset regional model, the suspicious region in the target video frame is detected；Or
According to the region in the reference frame there are abnormal conditions, the suspicious region in the target video frame is determined；Or
According to preset regional model, the alternative suspicious region in the target video frame is detected；And according to the reference Frame and the alternative suspicious region detected, determine the suspicious region in the target video frame.
In a kind of specific implementation of the application, the region according in the reference frame there are abnormal conditions, Determine the suspicious region in the target video frame, comprising:
According to the acquisition moment, the target video frame F is obtainedCPrevious video frame FFIt is middle that there are the regions of abnormal conditions；
Determine the video frame FFIt is middle that there are the regions of abnormal conditions in the target video frame FCIn corresponding region；
Belong to the number of the pixel in the sport foreground region of the target video frame in each region determined by counting；
Judge whether the number for each pixel that statistics obtains meets following formula:
NumFAm/NumTAm< ThP,
Wherein, NumFamBelong to the picture in the sport foreground region of the target video frame in any region m determined by indicating The number of vegetarian refreshments, NumTamIndicate the total number of pixel in the region m, ThPIndicate preset first pixel number ratio Threshold value；
If satisfied, determining that the corresponding region of pixel number is the suspicious region in the target video frame.
It is described according to preset regional model in a kind of specific implementation of the application, detect the target video Alternative suspicious region in frame, comprising:
Determine the foreground area in the target video frame；
According to preset regional model, alternative suspicious region is detected in the foreground area.
It is described according to the reference frame and the alternative suspicious area detected in a kind of specific implementation of the application Domain determines the suspicious region in the target video frame, comprising:
Determine the target video frame FCPrevious video frame FFIn area identical with the alternative suspicious region position detected Domain；
Belong to the video frame F in the pixel of each region determined by obtainingFIt is middle there are the region of abnormal conditions The number of pixel；
Determine that meeting the corresponding alternative suspicious region in region of following formula in above-mentioned identified region is the mesh The suspicious region in video frame is marked,
Na/Nt> TN,
Wherein, NaBelong to the video frame F in any region S determined by indicatingFIt is middle that there are the pictures in the region of abnormal conditions The number of vegetarian refreshments, NtIndicate the number of pixel in the region S, TNIndicate preset second pixel number proportion threshold value.
Personage in a kind of specific implementation of the application, in the detection target video frame, comprising:
According to current time and/or present intensity, person detecting model is selected from preset person detecting model library；
According to the personage in selected person detecting model inspection target video frame.
In a kind of specific implementation of the application, personage position of the personage detected by the acquisition in reference frame It sets, comprising:
Obtain personage associated with detected personage in reference frame；
According to the similarity degree and movement velocity between detected personage personage associated with it, calculating is detected The confidence level of personage out, wherein the confidence level, for indicating that a personage personage associated there is same personage's Credibility；
It obtains confidence level in detected personage and is greater than the personage of preset confidence threshold value in the reference frame Character positions；
The personage according to detected by and the character positions in the reference frame, determine the target video frame Whether suspicious region is region there are abnormal conditions, comprising:
It is greater than in personage and the reference frame of preset confidence threshold value according to confidence level in detected personage Character positions, determine whether the suspicious region of the target video frame is region there are abnormal conditions.
In a kind of specific implementation of the application, the information detecting method further include:
In the suspicious region for determining the target video frame, there are in the case where abnormal conditions, obtain the suspicious region It is confirmed as the number in the region there are abnormal conditions in the video frame of acquisition；
In the case where number obtained meets preset monitoring condition, prompt messages are sent.
In order to achieve the above objectives, the embodiment of the present application discloses a kind of information detector, and described device includes:
Person detecting module, for detecting the personage in target video frame；
Position obtains module, for obtaining character positions of the detected personage in reference frame, wherein the reference Frame are as follows: the acquisition moment is located at the preset quantity video frame before the acquisition moment of the target video frame；
Suspicious region detection module, for according to preset Region detection algorithms, detect in the target video frame can Doubt region；
Abnormal area determining module, for according to the character positions in detected personage and the reference frame, really Whether the suspicious region of the fixed target video frame is region there are abnormal conditions.
In a kind of specific implementation of the application, the abnormal area determining module, comprising:
Character positions obtain submodule, for obtaining personage position of the detected personage in the target video frame It sets；
Suspicious figure determines submodule, for according in the character positions and the reference frame in the target video frame Character positions determine the suspicious figure in detected personage；
Corresponding region obtains submodule, in the suspicious region for obtaining the reference frame with the target video frame can Doubt the corresponding region in region；
Apart from computational submodule, for calculating the suspicious figure and the target video frame in the target video frame The distance between suspicious region, and calculate in the reference frame between the suspicious figure and region obtained away from From；
Abnormal area determines submodule, for determining whether the suspicious region of the target video frame is that there are abnormal conditions Region.
In a kind of specific implementation of the application, the suspicious figure determines submodule, comprising:
First information judging unit meets expression formula one for judging whether,
Wherein, the expression formula one are as follows:
meand> TmAnd vard< Tv1,
meandIndicate the mean value of the mean deviation distance of detected each personage, vardIt is each detected by indicating The variance of the mean deviation distance of personage, TmIndicate preset mean value threshold value, Tv1It indicates preset first variance threshold value, is detected The mean deviation distance of any personage i out indicates that the personage i is acquired in the target video frame and the reference frame The average value of moving distance between moment adjacent two frames；
Second information judging unit, for sentencing in the case where the judging result of the first information judging unit is no It is disconnected whether to meet expression formula two,
Wherein, the expression formula two are as follows:
varp< Tv2And vard< Tv3,
varpIndicate the variance of the character positions in the target video frame, Tv2Indicate preset second variance threshold value, Tv3 Indicate preset third variance threshold values；
Suspicious figure's determination unit, for the judging result of second information judging unit be it is no in the case where, root Determine mobile slow personage from detected personage according to expression formula three, and according to expression formula four from the slow personage of the movement Middle determining suspicious figure,
Wherein, the expression formula three are as follows:
frmd> Tcnt1And distbias< Tdist1,
frmdAny personage j in personage detected by indicating goes out in the target video frame and the reference frame Existing number, distbiasIndicate the mean deviation distance of the personage j, Tdist1Indicate preset first offset distance threshold value, Tcnt1Indicate preset first amount threshold；
The expression formula four are as follows:
distrela< Tdist2And frms> Tcnt2,
distrelaIndicate position and the pos of the slow personage k of any movementaverThe distance between, posaverIndicate each shifting The history deflection for moving slow personage most locates position pos slowlyparLocation mean value, posparIndicate the slow personage k of any movement The position in video frame f is acquired, the personage k is moved to the moving distance of the video frame f from the former frame of the video frame f Are as follows: the minimum value of moving distance of the personage k between acquisition moment adjacent two video frames acquired, frmsIndicate institute State the number that personage k is confirmed as slowly mobile personage in the video frame acquired, Tdist2Indicate preset second offset distance From threshold value, Tcnt2Indicate preset second amount threshold.
In a kind of specific implementation of the application, the suspicious region detection module is specifically used for according to preset Regional model detects the suspicious region in the target video frame；Or
The suspicious region detection module, specifically for determining according to the region in the reference frame there are abnormal conditions Suspicious region in the target video frame；Or
The suspicious region detection module, comprising:
Alternative suspicious region detection sub-module, for detecting in the target video frame according to preset regional model Alternative suspicious region；
First suspicious region determines submodule, for determining according to the reference frame and the alternative suspicious region detected Suspicious region in the target video frame.
In a kind of specific implementation of the application, the suspicious region detection module, comprising:
Abnormal area obtains submodule, for obtaining the target video frame F according to the acquisition momentCPrevious video frame FF It is middle that there are the regions of abnormal conditions；
Corresponding region determines submodule, for determining the video frame FFIt is middle that there are the regions of abnormal conditions in the target Corresponding region in video frame；
Pixel number statistic submodule, for counting the fortune for belonging to the target video frame in identified each region The number of the pixel of dynamic foreground area；
Ratio judging submodule, for judging whether the number for counting obtained each pixel meets following formula:
NumFAm/NumTAm< ThP,
Wherein, NumFamBelong to the picture in the sport foreground region of the target video frame in any region m determined by indicating The number of vegetarian refreshments, NumTamIndicate the total number of pixel in the region m, ThPIndicate preset first pixel number ratio Threshold value；
Second suspicious region determines submodule, is the case where being for the judging result in the ratio judging submodule Under, determine that the corresponding region of pixel number is the suspicious region in the target video frame.
In a kind of specific implementation of the application, the alternative suspicious region detection sub-module, comprising:
Foreground area determination unit, for determining the foreground area in the target video frame；
Alternative suspicious region detection unit, for being detected in the foreground area alternative according to preset regional model Suspicious region.
In a kind of specific implementation of the application, first suspicious region determines submodule, comprising:
Position same area determination unit, for determining the target video frame FCPrevious video frame FFIn with detect The identical region in alternative suspicious region position；
Pixel number obtaining unit belongs to the video frame F in the pixel for each region determined by obtainingF It is middle that there are the numbers of the pixel in the region of abnormal conditions；
Suspicious region determination unit, for determining that the region for meeting following formula in above-mentioned identified region is corresponding Alternative suspicious region is the suspicious region in the target video frame,
Na/Nt> TN,
Wherein, NaBelong to the video frame F in any region S determined by indicatingFIt is middle that there are the pictures in the region of abnormal conditions The number of vegetarian refreshments, NtIndicate the number of pixel in the region S, TNIndicate preset second pixel number proportion threshold value.
In a kind of specific implementation of the application, the person detecting module, comprising:
Person detecting model selects submodule, is used for according to current time and/or present intensity, from preset person detecting Person detecting model is selected in model library；
Person detecting submodule, for according to the personage in selected person detecting model inspection target video frame.
In a kind of specific implementation of the application, the position obtains module, comprising:
It is associated with personage and obtains submodule, for obtaining personage associated with detected personage in reference frame；
Confidence calculations submodule, for according to the similarity degree between detected personage personage associated with it with And movement velocity, calculate the confidence level of detected personage, wherein the confidence level is associated therewith for indicating a personage The personage of connection is the credibility of same personage；
Position obtains submodule, the people for being greater than preset confidence threshold value for obtaining confidence level in detected personage The character positions of object in the reference frame；
The abnormal area determining module, specifically for being greater than preset confidence according to confidence level in detected personage The personage for spending threshold value and the character positions in the reference frame, determine whether the suspicious region of the target video frame is presence The region of abnormal conditions.
In a kind of specific implementation of the application, the information detector further include:
Number obtains module, for determine the suspicious region of the target video frame there are in the case where abnormal conditions, Obtain the number in the region that the suspicious region is confirmed as there are abnormal conditions in the video frame acquired；
Prompt messages sending module, for sending out in the case where number obtained meets preset monitoring condition Send prompt messages.
As seen from the above, in scheme provided by the embodiments of the present application, first detection target video frame in personage and this A little character positions of the personage in reference frame, then the suspicious region in target video frame is detected, finally combine detected people Character positions in object and reference frame determine whether the suspicious region of target video frame is region there are abnormal conditions.It can See and scheme provided by the embodiments of the present application is applied to be capable of detecting when the region in video frame there are abnormal conditions, is not necessarily to staff The region there are abnormal conditions is found by way of patrol, can reduce the operating pressure of staff.
Detailed description of the invention
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, to embodiment or will show below There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this Some embodiments of application for those of ordinary skill in the art without creative efforts, can be with It obtains other drawings based on these drawings.
Fig. 1 is the flow diagram of the first information detecting method provided by the embodiments of the present application；
Fig. 2 is the flow diagram of second of information detecting method provided by the embodiments of the present application；
Fig. 3 is the flow diagram of the third information detecting method provided by the embodiments of the present application；
Fig. 4 is the flow diagram of the 4th kind of information detecting method provided by the embodiments of the present application；
Fig. 5 is the structural schematic diagram of the first information detector provided by the embodiments of the present application；
Fig. 6 is the structural schematic diagram of second of information detector provided by the embodiments of the present application；
Fig. 7 is the structural schematic diagram of the third information detector provided by the embodiments of the present application；
Fig. 8 is the structural schematic diagram of the 4th kind of information detector provided by the embodiments of the present application.
Specific embodiment
Below in conjunction with the attached drawing in the embodiment of the present application, technical solutions in the embodiments of the present application carries out clear, complete Site preparation description, it is clear that described embodiments are only a part of embodiments of the present application, instead of all the embodiments.It is based on Embodiment in the application, it is obtained by those of ordinary skill in the art without making creative efforts every other Embodiment shall fall in the protection scope of this application.
Fig. 1 is the flow diagram of the first information detecting method provided by the embodiments of the present application, this method comprises:
S101: the personage in detection target video frame.
Above-mentioned target video frame can be the image collected in real time by image capture device, wherein Image Acquisition Equipment can be the image capture devices such as common ball machine in video monitoring.Those skilled in the art it is understood that Multiple presetting bits can be set for a ball machine in practical application, it is corresponding to each presetting bit respectively according to the preset time interval Region carry out Image Acquisition.It should be noted that in the case where above-mentioned image capture device is ball machine, using the application reality When the scheme progress infomation detection of example offer is provided, it can be understood as carry out information in the acquired image of a presetting bit for ball machine The case where detection.
Certainly, above-mentioned image capture device is not limited in ball machine, and the application is defined not to this.
It should be understood that detection target video frame in personage when, can by the human detection method based on statistics into Row detection needs to construct model by the human detection method based on statistics when being detected, and by constructing model when institute structure The factors such as the accuracy of established model and the scene of selected sample, intensity of illumination, brightness are related, therefore, can construct multiple moulds Then type selects different models to be detected at different conditions, to improve the accuracy rate of person detecting.
It, can be first according to current time and/or present intensity, from pre- specifically, when personage in detection target video frame If person detecting model library in select person detecting model, then according to selected person detecting model inspection target video Personage in frame.
For example, may include using daytime in above-mentioned preset person detecting model library as the pedestrian dummy of background and with night For the pedestrian dummy etc. of background, it is, of course, also possible to include using fine day as the pedestrian dummy of background, using the cloudy day as the pedestrian of background Model etc., the application are defined not to this.
S102: character positions of the detected personage in reference frame are obtained.
Wherein, above-mentioned reference frame it is to be understood that acquisition the moment be located at target video frame acquisition the moment before preset The value of quantity video frame, above-mentioned preset quantity is generally higher than equal to 1.
Since image capture device is to carry out Image Acquisition according to fixed time interval, and between this set time Every typically small, for example, 0.04 second etc., so, it is usually identical when image capture device carries out Image Acquisition to Same Scene Personage appear in continuous multiple frames image, so, the personage in S101 in detected target video frame generally can be Acquisition the moment be located at the acquisition moment of target video frame before several video frames in occur.
Above-mentioned preset quantity can be determined according to practical situations, for example, it may be 5,10,20 etc..
It, can be according to these location informations obtained after obtaining character positions of the detected personage in reference frame The information such as the detected motion profile of each personage are analyzed, may include: the movement of personage in the motion track information The information such as path, movement velocity, further can analyze out the personage according to the motion profile of personage is to fast forward through, slowly Speed advances, hovers or static etc..
It should be noted that above-mentioned reference frame and target video frame are the video frames for same presetting bit, or it is referred to as For the video frame for Same Scene.
S103: according to preset Region detection algorithms, the suspicious region in target video frame is detected.
It should be noted that Region detection algorithms belong to the technology of comparative maturity, those skilled in the art being capable of root It is easy to know a variety of Region detection algorithms according to the prior art, no longer repeat one by one here, more typical Region detection algorithms have CNN (Convolutional Neural Networks, convolutional neural networks) Region detection algorithms etc..
Above-mentioned suspicious region can be doubtful operator in the stand region of outdoor setting, the parking stall area in doubtful parking lot Domain etc., the application are not defined the specific appearance form of suspicious region.
Specifically, according to preset Region detection algorithms, it, can be according to pre- when detecting the suspicious region in target video frame If regional model, detect the suspicious region in the target video frame, in which, target video frame can be carry out image The first frame of acquisition, naturally it is also possible to be the non-first frame for carrying out Image Acquisition, the application is defined not to this.
In addition, those skilled in the art are it is understood that have the time between acquisition moment adjacent video frame Correlation and spatial coherence, that is to say, that can be with reference target video frame when detecting the suspicious region in target video frame Reference frame or in which region there are abnormal conditions, wherein the frame number of referenced reference frame can be a frame, be also possible to more Frame, the application not to specific reference to frame number be defined.
In a kind of specific implementation of the application, according to the region in reference frame there are abnormal conditions, target is determined When suspicious region in video frame, target video frame F can be obtained first according to the acquisition momentCPrevious video frame FFIn there are different The region of reason condition determines video frame FFIt is middle that there are the regions of abnormal conditions in target video frame FCIn corresponding region, statistics is true Belong to the number of the pixel in the sport foreground region of target video frame in fixed each region, then judgement statistics obtains every Whether the number of one pixel meets following formula: NumFAm/NumTAm< ThP, if satisfied, determining that the pixel number is corresponding Region be target video frame in suspicious region.
For the case where above-mentioned abnormal conditions are to manage stand, since stand is usually static constant, so, when When judging to count obtained any pixel point number to meet above-mentioned expression formula, illustrate the pixel number pair in target video frame A possibility that region answered is static stand is higher, hence, it can be determined that the corresponding region of pixel number is target video Suspicious region in frame.
It should be noted that the specific implementation is mainly used in the case where non-first frame that Image Acquisition obtains.
Those skilled in the art are for a long time under normal circumstances it is understood that for static stand It remains static, so same static stand region generally will appear and be in multiple continuous video frames Stationary state in a kind of relatively good implementation of the application, can also judge obtained each in light of this situation In the number of the pixel in the corresponding sport foreground region for belonging to target video frame in region and the region between pixel sum Ratio be less than preset first pixel number proportion threshold value after, judge the region acquisition the moment be located at target video frame Whether the number for being confirmed as the region there are abnormal conditions in video frame before is greater than preset numerical value, if more than then really The fixed region is the suspicious region in target video frame in the corresponding region in target video frame.
Since for Same Scene, background area is almost unchanged, so, the movement in above-mentioned target video frame Foreground area can use to be obtained in such a way that the background model that adaptive mode constructs extracts sport foreground region, in addition, For the accuracy for guaranteeing background model, above-mentioned back can also be constantly updated according to image capture device each frame image collected Scape model.
In addition, referring to fig. 2, providing second of information detecting method in another specific implementation of the application Flow diagram in the present embodiment, according to preset Region detection algorithms, detect target video compared with previous embodiment Suspicious region (S103) in frame, comprising:
S103A: according to preset regional model, the alternative suspicious region in target video frame is detected.
It is similar with person detecting is carried out in S101 in target video frame, detect the alternative suspicious region in target video frame When can also be detected by model matching method, above-mentioned preset regional model can be to be constructed in advance.
For example, multiple operators can be obtained ahead of time in the image information of the stand of outdoor setting, machine may then pass through Device study the methods of building stand regional model, wherein in each image information being obtained ahead of time stand it is more representative more Help to construct preferable stand model, in addition, the image information being obtained ahead of time is more, more facilitates to construct preferable stand mould Type.
Under normal conditions, image capture device carries out Image Acquisition for Same Scene, image acquired in this way Background is almost unchanged, for example, street architecture object, retail shop's shop front etc., and prospect be then it is continually changing, therefore, detect target It can be detected based on the foreground area of target video when alternative suspicious region in video, specifically, according to preset area Domain model can first determine the foreground area in target video frame, then when detecting the alternative suspicious region in target video frame According to preset regional model, alternative suspicious region is detected in above-mentioned foreground area.
Since for Same Scene, background area is almost unchanged, so, it can be not present in practical application Image is acquired when abnormal conditions in advance as background model, when carrying out infomation detection later, by institute's acquired image with Above-mentioned background model carries out Difference Calculation, is partitioned into foreground area from institute's acquired image.
S103B: according to reference frame and the alternative suspicious region detected, the suspicious region in target video frame is determined.
It when determining the suspicious region in target video frame, can be determined according to predeterminated position method, specifically, if standby Suspicious region is selected to match with preset location information, then it is assumed that the alternative suspicious region is the suspicious area in target video frame Domain, above-mentioned preset location information can be according to the experience of operation and maintenance personnel setting etc..
In a kind of relatively good implementation of the application, according to reference frame and the alternative suspicious region detected, mesh is determined When marking the suspicious region in video frame, target video frame F can be first determinedCPrevious video frame FFIn with detect it is alternative can The identical region of regional location is doubted, obtains in the pixel of identified each region and belongs to video frame FFIn there are abnormal conditions Region pixel number, then determine it is above-mentioned determined by meet the region of following formula in region and corresponding alternatively may be used Doubting region is the suspicious region in target video frame,
Na/Nt> TN,
Wherein, NaBelong to video frame F in any region S determined by indicatingFIt is middle that there are the pixels in the region of abnormal conditions Number, NtIndicate the number of pixel in the S of region, TNIndicate preset second pixel number proportion threshold value.
It is stationary, thus above-mentioned there are abnormal conditions under normal conditions specifically, for managing stand Region can be understood as the region with this stationary characteristic, in this case Na/Nt> TNWhen, it is believed that suspicious area Domain is fixed, if it is fixed for being detected a certain region on the basis of meeting above-mentioned relation formula in continuous several frames Motionless, it is believed that the region is doubtful stand region.
S104: according to the character positions in detected personage and reference frame, the suspicious area of target video frame is determined Whether domain is region there are abnormal conditions.
It should be understood that above-mentioned suspicious region might not really there are the regions of abnormal conditions, so also need into One step judges whether the suspicious region of target video frame is region there are abnormal conditions.For example, above-mentioned abnormal conditions can be Operator is the stand of outdoor setting the case where, the case where the vehicle in parking lot crosses parking stall etc., and the application is not to upper The specific appearance form for stating abnormal conditions is defined.
Specifically, there are the characteristics that in practical application the regions of abnormal conditions in addition to its own mutually outside the Pass, it is also possible to meeting It is related to surrounding personage, for example, operator is normally near stand, and hover near stand etc..
In view of the foregoing, in a kind of optional implementation of the application, according to detected personage and reference Character positions in frame can be obtained first when whether the suspicious region for determining target video frame is the region there are abnormal conditions Character positions of the detected personage in target video frame, according in the character positions and reference frame in target video frame Character positions determine the suspicious figure in detected personage, then determine the suspicious region in reference frame, and obtain reference Region corresponding with the suspicious region of target video frame in the suspicious region of frame calculates suspicious figure and mesh in target video frame Mark the distance between the suspicious region of video frame, and calculated in reference frame between suspicious figure and region obtained away from From determining whether the suspicious region of target video frame is region there are abnormal conditions finally according to calculated distance.
It should be noted that scheme provided in this embodiment carries out infomation detection for target video frame, detected Cheng Zhong can detect the suspicious region in target video frame in S103.For reference frame, since reference frame is the acquisition moment Video frame before the acquisition moment of target video frame, so when carrying out infomation detection to target video frame, to ginseng It examines frame and carried out identical infomation detection, detection process is identical as to the target video frame progress process of infomation detection, therefore, For the suspicious region that can obtain reference frame during the infomation detection of reference frame.For convenience of each frame conduct in video sequence The reference frame of subsequent video frame, after carrying out infomation detection to each frame in video sequence, what can first be will test should The information of the suspicious region of video frame is locally stored, when reference frame of the video frame as other video frames, Ke Yizhi Connect the information that the suspicious region of the video frame is obtained from the information being locally stored.
Optionally, according to calculated distance, determine whether the suspicious region of target video frame is that there are abnormal conditions Region when, can distance obtained by calculation mean value, determine whether the suspicious region of target video frame is that there are exceptions The region of situation, specifically, can be in the case where the mean value of above-mentioned calculated distance is less than preset distance threshold, The suspicious region for thinking target video frame is the region there are abnormal conditions, opposite, in the equal of above-mentioned calculated distance Value is not less than in the case where preset distance threshold, it is believed that the suspicious region of target video frame is that there is no the areas of abnormal conditions Domain.
In addition, when whether the suspicious region for determining target video frame is the region there are abnormal conditions, in addition to can root Except being determined according to the mean value of above-mentioned calculated distance, it is also contemplated that the information such as variance of above-mentioned calculated distance, The application is defined not to this.
In a kind of relatively good implementation of the application, according to the people in the character positions and reference frame in target video frame Object location determines the suspicious figure in detected personage, can be determined by following steps:
Judge whether to meet expression formula one,
Wherein, above-mentioned expression formula one are as follows:
meand> TmAnd vard< Tv1,
meandIndicate the mean value of the mean deviation distance of detected each personage, vardIt is each detected by indicating The variance of the mean deviation distance of personage, TmIndicate preset mean value threshold value, Tv1It indicates preset first variance threshold value, is detected The mean deviation distance of any personage i out indicates that personage i acquires moment adjacent two in target video frame and reference frame The average value of moving distance between frame；
Meeting above-mentioned expression formula for the moment, it can be understood as personage is mobile in collective；
And it is being unsatisfactory for above-mentioned expression formula for the moment, it continues to determine whether to meet expression formula two,
Wherein, above-mentioned expression formula two are as follows:
varp< Tv2And vard< Tv3,
varpIndicate the variance of the character positions in target video frame, Tv2Indicate preset second variance threshold value, Tv3It indicates Preset third variance threshold values；
When meeting above-mentioned expression formula two, it can be understood as current scene is personage's focusing field scape；
When being unsatisfactory for expression formula two, mobile slow personage is determined from detected personage according to expression formula three, and Suspicious figure is determined from the slow personage of above-mentioned movement according to expression formula four,
Wherein, above-mentioned expression formula three are as follows:
frmd> Tcnt1And distbias< Tdist1,
frmdTime that any personage j in personage detected by indicating occurs in target video frame and reference frame Number, distbiasIndicate the mean deviation distance of personage j, Tdist1Indicate preset first offset distance threshold value, Tcnt1Indicate default The first amount threshold；
Above-mentioned expression formula four are as follows:
distrela< Tdist2And frms> Tcnt2,
distrelaIndicate position and the pos of the slow personage k of any movementaverThe distance between, posaverIndicate each shifting The history deflection for moving slow personage most locates position pos slowlyparLocation mean value, posparIndicate the slow personage k of any movement The position in video frame f is acquired, personage k is moved to the moving distance of video frame f from the former frame of video frame f are as follows: personage k is The minimum value of moving distance between acquisition moment adjacent two video frames of acquisition, frmsIndicate personage k in the view acquired It is confirmed as the number of slowly mobile personage, T in frequency framedist2Indicate preset second offset distance threshold value, Tcnt2It indicates Preset second amount threshold.
It is operator in the case where the stand of outdoor setting in above-mentioned abnormal conditions in practical application, above-mentioned suspicious people Object can be understood as operator, stall owner, above-mentioned in the case where the vehicle that above-mentioned abnormal conditions are parking lot crosses parking stall It can be understood as car owner with personage.
It should be noted that embodiment illustrated in fig. 2 is also mainly used in the case where non-first frame that Image Acquisition obtains.
As seen from the above, personage and these people in scheme provided in this embodiment, first in detection target video frame Character positions of the object in reference frame, then detect the suspicious region in target video frame, finally combine detected personage with And the character positions in reference frame, determine whether the suspicious region of target video frame is region there are abnormal conditions.It can be seen that answering The region in video frame there are abnormal conditions is capable of detecting when with scheme provided in this embodiment, passes through patrol without staff Mode find the region there are abnormal conditions, can reduce the operating pressure of staff.
In another specific implementation of the application, referring to Fig. 3, the process of the third information detecting method is provided Schematic diagram in the present embodiment, obtains detected personage at the acquisition moment and is located at target video frame compared with previous embodiment Acquisition the moment before preset quantity video frame in position (S102), comprising:
S102A: personage associated with detected personage in reference frame is obtained.
It is and above-mentioned pre- under normal conditions since image capture device is progress Image Acquisition according to the preset time interval If time interval it is typically small, so the probability that same personage appears in continuous multiple frames image is higher, but due to shooting The influence of the factors such as light, shooting angle, the travel speed of personage may be difficult to accurate detection under normal conditions and go out same people Position of the object in different images, in view of the foregoing, in a kind of situation, above-mentioned personage associated with detected personage Can be understood as may be with detected personage same personage personage.
S102B: it according to the similarity degree and movement velocity between detected personage personage associated with it, calculates The confidence level of detected personage.
Wherein, above-mentioned confidence level, for indicating that a personage personage associated there is the credibility of same personage.
S102C: it obtains confidence level in detected personage and is greater than the personage of preset confidence threshold value in reference frame Character positions.
Specifically, can by confidence level in detected personage greater than preset confidence threshold value Th1 personage and The segment that associated personage of the personage in reference frame is constituted is referred to as high confidence level segment, on the contrary, by detected people Associated personage structure of personage and the personage of the confidence level less than another preset confidence threshold value Th2 in reference frame in object At segment be referred to as low confidence segment.Further, subsequent can be according to above-mentioned high confidence level segment and low confidence Segment determines whether the suspicious region of target video frame is region there are abnormal conditions.
It should be noted that above-mentioned two confidence threshold value can be equal, and it can also be unequal, specifically, Th2 can be small In Th1.
According to the character positions in detected personage and reference frame, determine target video frame suspicious region whether For there are the region of abnormal conditions (S104), comprising:
S104A: it is greater than personage and the reference frame of preset confidence threshold value according to confidence level in detected personage In character positions, determine whether the suspicious region of target video frame is region there are abnormal conditions.
As seen from the above, in scheme provided in this embodiment, it is greater than according to confidence level in detected personage preset The personage of confidence threshold value and position obtained determine whether the suspicious region of target video frame is that there are abnormal conditions Region, rather than be determined according to detected all persons, therefore can subtract on the basis of guaranteeing that definitive result is accurate Few calculation amount, improves calculating speed.
In another specific implementation of the application, referring to fig. 4, the process of the 4th kind of information detecting method is provided Schematic diagram, compared with previous embodiment, in the present embodiment, above- mentioned information detection method further include:
S105: in the suspicious region for determining target video frame, there are in the case where abnormal conditions, obtain the suspicious region to exist It is confirmed as the number in the region there are abnormal conditions in the video frame acquired.
S106: in the case where number obtained meets preset monitoring condition, prompt messages are sent.
Specifically, above-mentioned preset monitoring condition can be and judge whether number obtained is greater than preset number threshold Value, if more than determining that number obtained meets preset monitoring condition, otherwise, it is determined that number obtained is unsatisfactory for presetting Monitoring condition.Above-mentioned preset frequency threshold value can be 0,1,2 etc..
As seen from the above, in scheme provided in this embodiment, there are abnormal feelings in the suspicious region for determining target video frame In the case where condition, prompt messages are sent, facilitate staff found the abnormal situation in time, in addition, suspicious region is true Be set to the region there are abnormal conditions number meet certain monitoring condition in the case where just send prompt messages, Neng Gouyou Effect reduces wrong report phenomenon.
Corresponding with above- mentioned information detection method, the embodiment of the present application provides a kind of information detector.
Fig. 5 is the structural schematic diagram of the first information detector provided by the embodiments of the present application, which includes:
Person detecting module 501, for detecting the personage in target video frame；
Position obtains module 502, for obtaining character positions of the detected personage in reference frame, wherein described Reference frame are as follows: the acquisition moment is located at the preset quantity video frame before the acquisition moment of the target video frame；
Suspicious region detection module 503, for detecting in the target video frame according to preset Region detection algorithms Suspicious region；
Abnormal area determining module 504, for according to the character positions in detected personage and the reference frame, Whether the suspicious region for determining the target video frame is region there are abnormal conditions.
Specifically, the abnormal area determining module 504 may include:
Character positions obtain submodule, for obtaining personage position of the detected personage in the target video frame It sets；
Suspicious figure determines submodule, for according in the character positions and the reference frame in the target video frame Character positions determine the suspicious figure in detected personage；
Corresponding region obtains submodule, in the suspicious region for obtaining the reference frame with the target video frame can Doubt the corresponding region in region；
Apart from computational submodule, for calculating the suspicious figure and the target video frame in the target video frame The distance between suspicious region, and calculate in the reference frame between the suspicious figure and region obtained away from From；
Abnormal area determines submodule, for determining whether the suspicious region of the target video frame is that there are abnormal conditions Region.
Specifically, the suspicious figure determines that submodule may include:
First information judging unit meets expression formula one for judging whether,
Wherein, the expression formula one are as follows:
meand> TmAnd vard< Tv1,
meandIndicate the mean value of the mean deviation distance of detected each personage, vardIt is each detected by indicating The variance of the mean deviation distance of personage, TmIndicate preset mean value threshold value, Tv1It indicates preset first variance threshold value, is detected The mean deviation distance of any personage i out indicates that the personage i is acquired in the target video frame and the reference frame The average value of moving distance between moment adjacent two frames；
Second information judging unit, for sentencing in the case where the judging result of the first information judging unit is no It is disconnected whether to meet expression formula two,
Wherein, the expression formula two are as follows:
varp< Tv2And vard< Tv3,
varpIndicate the variance of the character positions in the target video frame, Tv2Indicate preset second variance threshold value, Tv3 Indicate preset third variance threshold values；
Suspicious figure's determination unit, for the judging result of second information judging unit be it is no in the case where, root Determine mobile slow personage from detected personage according to expression formula three, and according to expression formula four from the slow personage of the movement Middle determining suspicious figure,
Wherein, the expression formula three are as follows:
frmd> Tcnt1And distbias< Tdist1,
frmdAny personage j in personage detected by indicating goes out in the target video frame and the reference frame Existing number, distbiasIndicate the mean deviation distance of the personage j, Tdist1Indicate preset first offset distance threshold value, Tcnt1Indicate preset first amount threshold；
The expression formula four are as follows:
distrela< Tdist2And frms> Tcnt2,
distrelaIndicate position and the pos of the slow personage k of any movementaverThe distance between, posaverIndicate each shifting The history deflection for moving slow personage most locates position pos slowlyparLocation mean value, posparIndicate the slow personage k of any movement The position in video frame f is acquired, the personage k is moved to the moving distance of the video frame f from the former frame of the video frame f Are as follows: the minimum value of moving distance of the personage k between acquisition moment adjacent two video frames acquired, frmsIndicate institute State the number that personage k is confirmed as slowly mobile personage in the video frame acquired, Tdist2Indicate preset second offset distance From threshold value, Tcnt2Indicate preset second amount threshold.
Specifically, the suspicious region detection module 503, can be specifically used for detecting institute according to preset regional model State the suspicious region in target video frame；Or
The suspicious region detection module 503 can be specifically used for according to the area in the reference frame there are abnormal conditions Domain determines the suspicious region in the target video frame；Or
The suspicious region detection module 503 can also include:
Alternative suspicious region detection sub-module 5031, for detecting the target video frame according to preset regional model In alternative suspicious region；
First suspicious region determines submodule 5032, for according to the reference frame and the alternative suspicious region that detects, Determine the suspicious region in the target video frame.
In a kind of optional implementation of the application, the suspicious region detection module 503 may include:
Abnormal area obtains submodule, for obtaining the target video frame F according to the acquisition momentCPrevious video frame FF It is middle that there are the regions of abnormal conditions；
Corresponding region determines submodule, for determining the video frame FFIt is middle that there are the regions of abnormal conditions in the target Corresponding region in video frame；
Pixel number statistic submodule belongs to the target video frame F for counting in identified each regionC's The number of the pixel in sport foreground region；
Ratio judging submodule, for judging whether the number for counting obtained each pixel meets following formula:
NumFAm/NumTAm< ThP,
Wherein, NumFamBelong to the picture in the sport foreground region of the target video frame in any region m determined by indicating The number of vegetarian refreshments, NumTamIndicate the total number of pixel in the region m, ThPIndicate preset first pixel number ratio Threshold value；
Second suspicious region determines submodule, is the case where being for the judging result in the ratio judging submodule Under, determine that the corresponding region of pixel number is the suspicious region in the target video frame.
In a kind of specific implementation of the application, referring to Fig. 6, the structure for providing second of information detector is shown It is intended to, compared with previous embodiment, in the present embodiment, the suspicious region detection module 503, comprising:
Alternative suspicious region detection sub-module 5031, for detecting the target video frame according to preset regional model In alternative suspicious region；
First suspicious region determines submodule 5032, for according to the reference frame and the alternative suspicious region that detects, Determine the suspicious region in the target video frame.
Specifically, the alternative suspicious region detection sub-module 5031 may include:
Foreground area determination unit, for determining the foreground area in the target video frame；
Alternative suspicious region detection unit, for being detected in the foreground area alternative according to preset regional model Suspicious region.
Specifically, first suspicious region determines that submodule 5032 may include:
Position same area determination unit, for determining the target video frame FCPrevious video frame FFIn with detect The identical region in alternative suspicious region position；
Pixel number obtaining unit belongs to the video frame F in the pixel for each region determined by obtainingF It is middle that there are the numbers of the pixel in the region of abnormal conditions；
Suspicious region determination unit, for determining that the region for meeting following formula in above-mentioned identified region is corresponding Alternative suspicious region is the suspicious region in the target video frame,
Na/Nt> TN,
Wherein, NaBelong to the video frame F in any region S determined by indicatingFIt is middle that there are the pictures in the region of abnormal conditions The number of vegetarian refreshments, NtIndicate the number of pixel in the region S, TNIndicate preset second pixel number proportion threshold value.
Specifically, the person detecting module 501 may include:
Person detecting model selects submodule, is used for according to current time and/or present intensity, from preset person detecting Person detecting model is selected in model library；
Person detecting submodule, for according to the personage in selected person detecting model inspection target video frame.
As seen from the above, personage and these people in scheme provided in this embodiment, first in detection target video frame Character positions of the object in reference frame, then detect the suspicious region in target video frame, finally combine detected personage with And the character positions of reference frame, determine whether the suspicious region of target video frame is region there are abnormal conditions.It can be seen that application Scheme provided in this embodiment is capable of detecting when the region in video frame there are abnormal conditions, passes through patrol without staff Mode finds the region there are abnormal conditions, can reduce the operating pressure of staff.
In another specific implementation of the application, referring to Fig. 7, the structure of the third information detector is provided Schematic diagram, compared with previous embodiment, in the present embodiment, the position obtains module 502, comprising:
It is associated with personage and obtains submodule 5021, for obtaining personage associated with detected personage in reference frame；
Confidence calculations submodule 5022, for according to the similar journey between detected personage personage associated with it Degree and movement velocity calculate the confidence level of detected personage, wherein the confidence level is for indicating a personage and its Associated personage is the credibility of same personage；
Position obtains submodule 5023, is greater than preset confidence threshold value for obtaining confidence level in detected personage Personage's character positions in the reference frame；
The abnormal area determining module 504, it is preset specifically for being greater than according to confidence level in detected personage Character positions in the personage of confidence threshold value and the reference frame, determine the target video frame suspicious region whether be There are the regions of abnormal conditions.
As seen from the above, in scheme provided in this embodiment, it is greater than according to confidence level in detected personage preset The personage of confidence threshold value and position obtained determine whether the suspicious region of target video is area there are abnormal conditions Domain, rather than be determined according to detected all persons, therefore can be reduced on the basis of guaranteeing that definitive result is accurate Calculation amount improves calculating speed.
In another specific implementation of the application, referring to Fig. 8, the structure of the 4th kind of information detector is provided Schematic diagram, compared with previous embodiment, in the present embodiment, above- mentioned information detection device further include:
Number obtains module 505, for the case where there are abnormal conditions for the suspicious region for determining the target video frame Under, obtain the number in the region that the suspicious region is confirmed as there are abnormal conditions in the video frame acquired；
Prompt messages sending module 506, in the case where number obtained meets preset monitoring condition, Send prompt messages.
As seen from the above, in scheme provided in this embodiment, there are abnormal feelings in the suspicious region for determining target video frame In the case where condition, prompt messages are sent, facilitate staff found the abnormal situation in time, in addition, suspicious region is true Be set to the region there are abnormal conditions number meet certain monitoring condition in the case where just send prompt messages, Neng Gouyou Effect reduces wrong report phenomenon.
For device embodiment, since it is substantially similar to the method embodiment, related so being described relatively simple Place illustrates referring to the part of embodiment of the method.
It should be noted that, in this document, relational terms such as first and second and the like are used merely to a reality Body or operation are distinguished with another entity or operation, are deposited without necessarily requiring or implying between these entities or operation In any actual relationship or order or sequence.Moreover, the terms "include", "comprise" or its any other variant are intended to Non-exclusive inclusion, so that the process, method, article or equipment including a series of elements is not only wanted including those Element, but also including other elements that are not explicitly listed, or further include for this process, method, article or equipment Intrinsic element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that There is also other identical elements in process, method, article or equipment including the element.
Those of ordinary skill in the art will appreciate that all or part of the steps in realization above method embodiment is can It is completed with instructing relevant hardware by program, the program can store in computer-readable storage medium, The storage medium designated herein obtained, such as: ROM/RAM, magnetic disk, CD.
The foregoing is merely the preferred embodiments of the application, are not intended to limit the protection scope of the application.It is all Any modification, equivalent replacement, improvement and so within spirit herein and principle are all contained in the protection scope of the application It is interior.

Claims (18)

1. a kind of information detecting method, which is characterized in that the described method includes:
Detect the personage in target video frame；
Obtain character positions of the detected personage in reference frame, wherein the reference frame are as follows: the acquisition moment is located at described Preset quantity video frame before the acquisition moment of target video frame；
According to preset Region detection algorithms, the suspicious region in the target video frame is detected；
According to the character positions in detected personage and the reference frame, the suspicious region of the target video frame is determined It whether is region there are abnormal conditions；
Wherein, the personage according to detected by and the character positions in the reference frame, determine the target video frame Suspicious region whether be region there are abnormal conditions, comprising:
Obtain character positions of the detected personage in the target video frame；
According to the character positions in the character positions and the reference frame in the target video frame, detected personage is determined In suspicious figure；
Determine the suspicious region in the reference frame；
Obtain region corresponding with the suspicious region of the target video frame in the suspicious region of the reference frame；
Calculated in the target video frame suspicious figure between the suspicious region of the target video frame at a distance from, and The distance between the suspicious figure and region obtained are calculated in the reference frame；
According to calculated distance, determine whether the suspicious region of the target video frame is region there are abnormal conditions.
2. the method according to claim 1, wherein the character positions according in the target video frame and Character positions in the reference frame determine the suspicious figure in detected personage, comprising:
Judge whether to meet expression formula one,
Wherein, the expression formula one are as follows:
meand> TmAnd vard< Tv1,
meandIndicate the mean value of the mean deviation distance of detected each personage, vardIndicate detected each personage Mean deviation distance variance, TmIndicate preset mean value threshold value, Tv1Indicate preset first variance threshold value, it is detected The mean deviation distance of any personage i indicates that the personage i acquires the moment in the target video frame and the reference frame The average value of moving distance between two adjacent frames；
If not satisfied, judge whether to meet expression formula two,
Wherein, the expression formula two are as follows:
varp< Tv2And vard< Tv3,
varpIndicate the variance of the character positions in the target video frame, Tv2Indicate preset second variance threshold value, Tv3It indicates Preset third variance threshold values；
If not satisfied, mobile slow personage is determined from detected personage according to expression formula three, and according to expression formula four from Suspicious figure is determined in the slow personage of movement,
Wherein, the expression formula three are as follows:
frmd> Tcnt1And distbias< Tdist1,
frmdWhat any personage j in personage detected by indicating occurred in the target video frame and the reference frame Number, distbiasIndicate the mean deviation distance of the personage j, Tdist1Indicate preset first offset distance threshold value, Tcnt1Table Show preset first amount threshold；
The expression formula four are as follows:
distrela< Tdist2And frms> Tcnt2,
distrelaIndicate position and the pos of the slow personage k of any movementaverThe distance between, posaverIndicate that each movement is slow The history deflection of slow personage most locates position pos slowlyparLocation mean value, posparIndicate that the slow personage k of any movement is being acquired Position in video frame f, the personage k are moved to the moving distance of the video frame f from the former frame of the video frame f are as follows: The minimum value of moving distance of the personage k between acquisition moment adjacent two video frames acquired, frmsDescribed in expression Personage k is confirmed as the number of slowly mobile personage, T in the video frame acquireddist2Indicate preset second offset distance Threshold value, Tcnt2Indicate preset second amount threshold.
3. the method according to claim 1, wherein described according to preset Region detection algorithms, described in detection Suspicious region in target video frame, comprising:
According to preset regional model, the suspicious region in the target video frame is detected；Or
According to the region in the reference frame there are abnormal conditions, the suspicious region in the target video frame is determined；Or
According to preset regional model, the alternative suspicious region in the target video frame is detected；And according to the reference frame and The alternative suspicious region detected determines the suspicious region in the target video frame.
4. according to the method described in claim 3, it is characterized in that, the area according in the reference frame there are abnormal conditions Domain determines the suspicious region in the target video frame, comprising:
According to the acquisition moment, the target video frame F is obtainedCPrevious video frame FFIt is middle that there are the regions of abnormal conditions；
Determine the video frame FFIt is middle that there are the regions of abnormal conditions in the target video frame FCIn corresponding region；
Belong to the number of the pixel in the sport foreground region of the target video frame in each region determined by counting；
Judge whether the number for each pixel that statistics obtains meets following formula:
NumFAm/NumTAm< ThP,
Wherein, NumFAmBelong to the pixel in the sport foreground region of the target video frame in any region m determined by indicating Number, NumTAmIndicate the total number of pixel in the region m, ThPIndicate preset first pixel number ratio threshold Value；
If satisfied, determining that the corresponding region of pixel number is the suspicious region in the target video frame.
5. according to the method described in claim 3, detecting the target it is characterized in that, described according to preset regional model Alternative suspicious region in video frame, comprising:
Determine the foreground area in the target video frame；
According to preset regional model, alternative suspicious region is detected in the foreground area.
6. the method according to claim 3 or 5, which is characterized in that it is described according to the reference frame and detect it is alternative Suspicious region determines the suspicious region in the target video frame, comprising:
Determine the target video frame FCPrevious video frame FFIn region identical with the alternative suspicious region position detected；
Belong to the video frame F in the pixel of each region determined by obtainingFIt is middle that there are the pixels in the region of abnormal conditions Number；
It determines and meets the corresponding alternative suspicious region in region of following formula in above-mentioned identified region for target view Suspicious region in frequency frame,
Na/Nt> TN,
Wherein, NaBelong to the video frame F in any region S determined by indicatingFIt is middle that there are the pixels in the region of abnormal conditions Number, NtIndicate the number of pixel in the region S, TNIndicate preset second pixel number proportion threshold value.
7. the method according to claim 1, wherein the personage in the detection target video frame, comprising:
According to current time and/or present intensity, person detecting model is selected from preset person detecting model library；
According to the personage in selected person detecting model inspection target video frame.
8. the method according to claim 1, wherein people of the personage detected by the acquisition in reference frame Object location, comprising:
Obtain personage associated with detected personage in reference frame；
According to the similarity degree and movement velocity between detected personage personage associated with it, calculate detected The confidence level of personage, wherein the confidence level, for indicating that a personage personage associated there is the credible of same personage Degree；
It obtains confidence level in detected personage and is greater than the personage of the personage of preset confidence threshold value in the reference frame Position；
The personage according to detected by and the character positions in the reference frame, determine the suspicious of the target video frame Whether region is region there are abnormal conditions, comprising:
It is greater than the people in the personage and the reference frame of preset confidence threshold value according to confidence level in detected personage Object location determines whether the suspicious region of the target video frame is region there are abnormal conditions.
9. the method according to claim 1, wherein the method also includes:
In the suspicious region for determining the target video frame, there are in the case where abnormal conditions, obtain the suspicious region acquiring Video frame in be confirmed as the number in region there are abnormal conditions；
In the case where number obtained meets preset monitoring condition, prompt messages are sent.
10. a kind of information detector, which is characterized in that described device includes:
Person detecting module, for detecting the personage in target video frame；
Position obtains module, for obtaining character positions of the detected personage in reference frame, wherein the reference frame Are as follows: the acquisition moment is located at the preset quantity video frame before the acquisition moment of the target video frame；
Suspicious region detection module, for detecting the suspicious area in the target video frame according to preset Region detection algorithms Domain；
Abnormal area determining module, for determining institute according to the character positions in detected personage and the reference frame Whether the suspicious region for stating target video frame is region there are abnormal conditions；
Wherein, the abnormal area determining module, comprising:
Character positions obtain submodule, for obtaining character positions of the detected personage in the target video frame；
Suspicious figure determines submodule, for according to the personage in the character positions and the reference frame in the target video frame Position determines the suspicious figure in detected personage；
Corresponding region obtains submodule, the suspicious area in the suspicious region for obtaining the reference frame with the target video frame The corresponding region in domain；
It, can for calculate the suspicious figure and the target video frame in the target video frame apart from computational submodule The distance between region is doubted, and calculates the distance between the suspicious figure and region obtained in the reference frame；
Abnormal area determines submodule, for determining whether the suspicious region of the target video frame is area there are abnormal conditions Domain.
11. device according to claim 10, which is characterized in that the suspicious figure determines submodule, comprising:
First information judging unit meets expression formula one for judging whether,
Wherein, the expression formula one are as follows:
meand> TmAnd vard< Tv1,
meandIndicate the mean value of the mean deviation distance of detected each personage, vardIndicate detected each personage Mean deviation distance variance, TmIndicate preset mean value threshold value, Tv1Indicate preset first variance threshold value, it is detected The mean deviation distance of any personage i indicates that the personage i acquires the moment in the target video frame and the reference frame The average value of moving distance between two adjacent frames；
Second information judging unit, in the case where the judging result of the first information judging unit is no, judgement to be It is no to meet expression formula two,
Wherein, the expression formula two are as follows:
varp< Tv2And vard< Tv3,
varpIndicate the variance of the character positions in the target video frame, Tv2Indicate preset second variance threshold value, Tv3It indicates Preset third variance threshold values；
Suspicious figure's determination unit, for the judging result of second information judging unit be it is no in the case where, according to table Mobile slow personage is determined from detected personage up to formula three, and true from the slow personage of the movement according to expression formula four Determine suspicious figure,
Wherein, the expression formula three are as follows:
frmd> Tcnt1And distbias< Tdist1,
frmdWhat any personage j in personage detected by indicating occurred in the target video frame and the reference frame Number, distbiasIndicate the mean deviation distance of the personage j, Tdist1Indicate preset first offset distance threshold value, Tcnt1Table Show preset first amount threshold；
The expression formula four are as follows:
distrela< Tdist2And frms> Tcnt2,
distrelaIndicate position and the pos of the slow personage k of any movementaverThe distance between, posaverIndicate that each movement is slow The history deflection of slow personage most locates position pos slowlyparLocation mean value, posparIndicate that the slow personage k of any movement is being acquired Position in video frame f, the personage k are moved to the moving distance of the video frame f from the former frame of the video frame f are as follows: The minimum value of moving distance of the personage k between acquisition moment adjacent two video frames acquired, frmsDescribed in expression Personage k is confirmed as the number of slowly mobile personage, T in the video frame acquireddist2Indicate preset second offset distance Threshold value, Tcnt2Indicate preset second amount threshold.
12. device according to claim 10, which is characterized in that
The suspicious region detection module, be specifically used for according to preset regional model, detect in the target video frame can Doubt region；Or
The suspicious region detection module, described in determining according to the region in the reference frame there are abnormal conditions Suspicious region in target video frame；Or
The suspicious region detection module, comprising:
Alternative suspicious region detection sub-module, for detecting alternative in the target video frame according to preset regional model Suspicious region；
First suspicious region determines submodule, described in determining according to the reference frame and the alternative suspicious region detected Suspicious region in target video frame.
13. device according to claim 12, which is characterized in that the suspicious region detection module, comprising:
Abnormal area obtains submodule, for obtaining the target video frame F according to the acquisition momentCPrevious video frame FFIn deposit In the region of abnormal conditions；
Corresponding region determines submodule, for determining the video frame FFIt is middle that there are the regions of abnormal conditions in the target video Corresponding region in frame；
Pixel number statistic submodule belongs to the target video frame F for counting in identified each regionCMovement The number of the pixel of foreground area；
Ratio judging submodule, for judging whether the number for counting obtained each pixel meets following formula:
NumFAm/NumTAm< ThP,
Wherein, NumFAmBelong to the pixel in the sport foreground region of the target video frame in any region m determined by indicating Number, NumTAmIndicate the total number of pixel in the region m, ThPIndicate preset first pixel number ratio threshold Value；
Second suspicious region determines submodule, for the judging result of the ratio judging submodule be in the case where, really The fixed corresponding region of pixel number is the suspicious region in the target video frame.
14. device according to claim 12, which is characterized in that the alternative suspicious region detection sub-module, comprising:
Foreground area determination unit, for determining the foreground area in the target video frame；
Alternative suspicious region detection unit is alternative suspicious for being detected in the foreground area according to preset regional model Region.
15. device described in 2 or 14 according to claim 1, which is characterized in that first suspicious region determines submodule, packet It includes:
Position same area determination unit, for determining the target video frame FCPrevious video frame FFIn with detect it is standby Select the identical region in suspicious region position；
Pixel number obtaining unit belongs to the video frame F in the pixel for each region determined by obtainingFIn deposit In the number of the pixel in the region of abnormal conditions；
Suspicious region determination unit, for determining that the region for meeting following formula in above-mentioned identified region is corresponding alternative Suspicious region is the suspicious region in the target video frame,
Na/Nt> TN,
Wherein, NaBelong to the video frame F in any region S determined by indicatingFIt is middle that there are the pixels in the region of abnormal conditions Number, NtIndicate the number of pixel in the region S, TNIndicate preset second pixel number proportion threshold value.
16. device according to claim 10, which is characterized in that the person detecting module, comprising:
Person detecting model selects submodule, is used for according to current time and/or present intensity, from preset person detecting model Person detecting model is selected in library；
Person detecting submodule, for according to the personage in selected person detecting model inspection target video frame.
17. device according to claim 10, which is characterized in that the position obtains module, comprising:
It is associated with personage and obtains submodule, for obtaining personage associated with detected personage in reference frame；
Confidence calculations submodule, for according to the similarity degree and fortune between detected personage personage associated with it Dynamic speed, calculates the confidence level of detected personage, wherein the confidence level is associated there for indicating a personage Personage is the credibility of same personage；
Position obtains submodule, exists for obtaining the personage that confidence level is greater than preset confidence threshold value in detected personage Character positions in the reference frame；
The abnormal area determining module, specifically for being greater than preset confidence level threshold according to confidence level in detected personage Character positions in the personage of value and the reference frame, determine whether the suspicious region of the target video frame is that there are exceptions The region of situation.
18. device according to claim 10, which is characterized in that described device further include:
Number obtains module, for, there are in the case where abnormal conditions, obtaining in the suspicious region for determining the target video frame The suspicious region is confirmed as the number in the region there are abnormal conditions in the video frame acquired；
Prompt messages sending module, for sending report in the case where number obtained meets preset monitoring condition Alert prompt information.
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