CN109040709A - Video monitoring method and device, monitoring server and video monitoring system - Google Patents
Video monitoring method and device, monitoring server and video monitoring system Download PDFInfo
- Publication number
- CN109040709A CN109040709A CN201811120075.8A CN201811120075A CN109040709A CN 109040709 A CN109040709 A CN 109040709A CN 201811120075 A CN201811120075 A CN 201811120075A CN 109040709 A CN109040709 A CN 109040709A
- Authority
- CN
- China
- Prior art keywords
- video
- monitoring
- target object
- target
- video data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Alarm Systems (AREA)
- Closed-Circuit Television Systems (AREA)
Abstract
The present invention relates to technical field of video monitoring, more particularly to a kind of video monitoring method and device, monitoring server and video monitoring system.Method includes: the following motion track of target object in predicted anomaly picture image when detecting abnormal picture image by the video data that target video camera is shot；Judge whether the following motion track of target object is detached from the monitoring area range of monitoring server；According to judging result, monitoring objective object.On the one hand, it can automatically detect in video with the presence or absence of abnormal picture image, video monitoring implemented with this, is fully and effectively monitored so as to perform to make target object in abnormal picture image in advance.On the other hand, it can also fully and effectively be monitored by the following motion track implementing monitoring of prediction target object to be further ensured that and make.
Description
Technical field
The present invention relates to technical field of video monitoring, more particularly to a kind of video monitoring method and device, monitoring service
Device and video monitoring system.
Background technique
Video monitoring is a kind of efficient monitoring technology, has the features such as real-time, reliability, intuitive, easy to use,
Thus receive the concern of all trades and professions.However traditional video monitoring system must have special personnel that real time monitoring is gone to regard
Frequently, need personnel actively to go to judge whether video has exception, cannot give warning in advance, can only be sent out in danger to the danger that may occur
Video is reviewed after life.Also, traditional approach can not look-ahead risk factor effectively monitored with making.
Summary of the invention
One purpose of the embodiment of the present invention is intended to provide a kind of video monitoring method and device, monitoring server and video prison
Control system can automatically detect out abnormal conditions to implement to effectively monitor.
In order to solve the above technical problems, the embodiment of the present invention the following technical schemes are provided:
In a first aspect, the embodiment of the present invention provides a kind of video monitoring method, which comprises
When detecting abnormal picture image by the video data that target video camera is shot, the abnormal picture image is predicted
The following motion track of middle target object；
Judge whether the following motion track of the target object is detached from the monitoring area range of the monitoring server；
According to judging result, the target object is monitored.
Optionally, described according to judging result, monitor the target object, comprising:
If the following motion track of the target object is detached from the monitoring area range of the monitoring server, shooting is determined
Range covers other video cameras of the following motion track of the target object；
Judge whether other video cameras with the target video camera connect same monitoring server；
If so, calling the video data of other video camera shootings；
If it is not, calling the video data for the other monitoring servers connecting with other video cameras, wherein described other
What the video data of monitoring server was transmitted from other video cameras to other monitoring servers；
If the following motion track of the target object continues to supervise without departing from the monitoring area range of the monitoring server
Control the target object.
Optionally, the video data for calling other video camera shootings, comprising:
Determine the target geographic position that the following motion track of the target object is related to；
The other monitoring servers for being located at other video cameras of the target geographic position to management send video calling and ask
It asks, so that other monitoring servers return to the video counts that other video cameras are shot according to the video call request
According to.
Optionally, the video data shot by target video camera detects abnormal picture image, comprising:
Obtain video detection Exception Model；
Judge whether picture image matches the video detection exception mould in the video data of the target video camera shooting
Type；
If matching, using the picture image as abnormal picture image；
If not matching, using the picture image as normal pictures image.
Optionally, the method also includes:
Training video data set is obtained, the training video data set includes the video data of a variety of abnormal scenes；
The video data of a variety of abnormal scenes is pre-processed；
Pretreated video data is handled by convolution algorithm, establishes the video detection Exception Model.
Optionally, the following motion track for predicting target object in the abnormal picture image, comprising:
Determine geographical location locating for target object in the abnormal picture image；
Obtain the topographic map in geographical location locating for the target object；
According to the current moving direction of the target object and the topographic map, predict that the future of the target object is mobile
Track.
In second aspect, the embodiment of the present invention provides a kind of video monitoring apparatus, and described device includes:
Prediction module when the video data for shooting by target video camera detects abnormal picture image, predicts institute
State the following motion track of target object in abnormal picture image；
Judgment module, for judging whether the following motion track of the target object is detached from the prison of the monitoring server
Control regional scope；
Monitoring module, for monitoring the target object according to judging result.
Optionally, the monitoring module is specifically used for:
If the following motion track of the target object is detached from the monitoring area range of the monitoring server, shooting is determined
Range covers other video cameras of the following motion track of the target object；
Judge whether other video cameras with the target video camera connect same monitoring server；
If so, calling the video data of other video camera shootings；
If it is not, calling the video data for the other monitoring servers connecting with other video cameras, wherein described other
What the video data of monitoring server was transmitted from other video cameras to other monitoring servers；
If the following motion track of the target object continues to supervise without departing from the monitoring area range of the monitoring server
Control the target object.
In the third aspect, the embodiment of the present invention provides a kind of monitoring server, comprising:
At least one processor；And
The memory being connect at least one described processor communication；Wherein, the memory be stored with can by it is described extremely
The instruction that a few processor executes, described instruction are executed by least one described processor, so that at least one described processing
Device can be used in executing described in any item video monitoring methods.
In fourth aspect, the embodiment of the present invention provides a kind of video monitoring system, comprising:
Several video cameras；
The monitoring server, the monitoring server and the video camera communicate.
At the 5th aspect, the embodiment of the present invention provides a kind of non-transient computer readable storage medium, the non-transient meter
Calculation machine readable storage medium storing program for executing is stored with computer executable instructions, and the computer executable instructions are for holding monitoring server
The described in any item video monitoring methods of row.
At the 6th aspect, the embodiment of the present invention provides a kind of computer program product, and the computer program product includes
The computer program being stored on non-volatile computer readable storage medium storing program for executing, the computer program include program instruction, when
When described program instructs monitored server to execute, the monitoring server is made to execute described in any item video monitoring methods.
In the video monitoring method and device, monitoring server and video monitoring system of each embodiment offer of the present invention
In, firstly, when detecting abnormal picture image by the video data that target video camera is shot, mesh in predicted anomaly picture image
Mark the following motion track of object；Secondly, judging whether the following motion track of target object is detached from the monitoring of monitoring server
Regional scope；Again, according to judging result, monitoring objective object.On the one hand, it can automatically detect in video with the presence or absence of different
Normal picture image implements video monitoring with this, makes comprehensively so as to perform in advance to target object in abnormal picture image
It effectively monitors.It on the other hand, can also be by the following motion track implementing monitoring of prediction target object, thus further
Guarantee, which is made, fully and effectively to be monitored.
Detailed description of the invention
One or more embodiments are illustrated by the picture in corresponding attached drawing, these exemplary theorys
The bright restriction not constituted to embodiment, the element in attached drawing with same reference numbers label are expressed as similar element, remove
Non- to have special statement, composition does not limit the figure in attached drawing.
Fig. 1 is that the embodiment of the present invention provides a kind of structural schematic diagram of video monitoring system；
Fig. 2 is that the embodiment of the present invention provides a kind of flow diagram of video monitoring method；
Fig. 3 is that the embodiment of the present invention provides a kind of structural schematic diagram of video monitoring apparatus；
Fig. 4 is that the embodiment of the present invention provides a kind of structural schematic diagram of monitoring server.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, not
For limiting the present invention.
The video monitoring method of the embodiment of the present invention, can be in any suitable type, the client with operational capability
It executes, such as in monitoring server, desktop computer, smart phone, tablet computer and other electronic products.Wherein, herein
Monitoring server can be a physical server or multiple physical servers it is virtual made of a logical server.Clothes
Business device be also possible to it is multiple can interconnected communication server composition server zone, and each functional module can be respectively distributed to take
It is engaged on each server in device group.
The video monitoring apparatus of the embodiment of the present invention can be used as software systems, be independently arranged in above-mentioned client,
It can be used as the one of functional module of integration in the processor, execute the video monitoring method of the embodiment of the present invention.
Referring to Fig. 1, Fig. 1 is that the embodiment of the present invention provides a kind of structural schematic diagram of video monitoring system.Such as Fig. 1 institute
Show, video monitoring system 100 includes several video cameras 11, monitoring server 12 and mobile terminal 13.
Video camera 11 is installed in predeterminable area, for acquiring video data.It is understood that video camera 11 is according to pre-
If rule is fixedly installed in predeterminable area, accomplish all to cover the predeterminable area as much as possible.For example, in the preset areas
Metope, ground, roof or the body surface in domain, in conjunction with the predeterminable area specific structure and block etc. and to lay the high definition
Video camera.
Each video camera forms a camera cluster, and for monitoring specifically monitored regional scope, each video camera is installed on
Predeterminated position in the specifically monitored regional scope.In general, each video camera all will be on the video data of acquisition in camera cluster
Reach same monitoring server.Different monitoring regional scope corresponds to different monitoring server.For managing different monitoring region
Different managers, the monitoring server of the two mutually not share monitor video.
For the shooting angle and coverage for improving video camera 11, the laying of video camera 11 is reduced, reduces system cost, it can
Catching in real time for HD video frame image is carried out to predeterminable area in such a way that use video camera 11 is in conjunction with multidimensional rotating electric machine to grab.
Of course, it is possible to select integrated video camera 11 to substitute the mode that multidimensional rotating electric machine is combined with video camera 11, for example, hemispherical
All-in-one machine, quick ball-type all-in-one machine, all-in-one machine in conjunction with built in the integrated high-definition camera or camera lens of holder etc., above-mentioned one
Body machine may be implemented to focus automatically.Preferably, selection has water-proof function, small volume, high resolution, high life and has
The high-definition camera of universal communication interface etc..
In some embodiments, video camera 11 is web camera, and video camera 11 is built-in with network code module.
Video camera includes that camera lens, imaging sensor, sound transducer, A/D converter, controller, control interface, network connect
Mouthful and etc..The video camera can be used for acquiring video data signal, and the video data signal is analog video signal.
The video camera is mainly made of CMOS photosensitive component and peripheral circuit, and the optical signal for the camera lens to be passed to is converted to
Electric signal.
Specifically, an embedded chip built in network code module, the embedded chip is for adopting the video camera
The video data signal collected is converted to digital signal, and the video data signal is analog video signal, the embedded core
Piece can also compress the digital signal.Specifically, the embedded chip can be Hi3516 Efficient Compression chip.
Video camera 11 sends monitoring server 12 for compressed digital signal by WIFI network.Monitoring server 12
Mobile terminal 13 can be sent by compressed digital signal.Wherein, video camera 11 further includes infrared sensor, so that camera shooting
Machine 11 has night vision function.User can directly with the camera review on browser viewing Web server or lead on network
It crosses mobile terminal APP directly to access, video camera 11 can more simply realize that monitoring, especially long-range monitoring have and simply apply
Work and maintenance, preferably support audio, preferably support alarm linkage, more flexible video recording storage, richer product selection,
The video effect of more high definition and more perfect monitoring management function, and video camera directly can be accessed into local area network, it is several
According to acquisition and photosignal end of convert, be whole network data provide end.
Wherein, monitoring server 12 is to provide the equipment of the service of calculating.The composition of monitoring server includes processor, hard
Disk, memory, system bus etc. are similar with general computer architecture, and monitoring server is responsible for providing the registration of mobile terminal APP
It logs in, the management of user, the functions such as equipment management.It is responsible for the store function of the video data of video camera simultaneously, and passes through prison
Control server remembers IP and the port of mobile terminal and video camera, and the IP and port of corresponding mobile terminal and video camera are passed
Other side is given, so that camera shooting generator terminal and mobile terminal be made to can know that IP and the port of other side, passes through IP address and the two is established in port
Connection communication.Then the video data that monitoring server obtains video camera removes analysis video data according to artificial intelligence module,
It will send a warning message when detecting abnormal video data and notify the mobile terminal.
Specifically, monitoring server 12 includes a processor, the processor includes artificial intelligence module.The artificial intelligence
Energy module is responsible for the real-time analysis to video data, at the time of detection is abnormal and notifies mobile terminal.The tool of artificial intelligence module
Body embodiment is divided into, the foundation of video abnormality detection model and two parts of application of video abnormality detection model.It is first
These three parts of the foundation of video abnormality detection model point, first part: the sets of video data of training video abnormality detection model,
Training and study for subsequent machine.Video data such as driving vehicle including various abnormal scenes frequently intert doubling,
Plunder, trail steal, fight, crowd fighting, shriek, sobs, smog, a variety of needs such as noisy video data detect
Abnormal scene.Training video data set covers most application scenarios.Second part: the pretreatment of sets of video data will regard
Frequency is converted to the picture of long 255 pixels and wide 255 pixel according to one second 10 picture of extraction, every picture is pressed.Part III:
The foundation of training pattern, using the convolution algorithm of artificial intelligence, Python code establishes the model of training.Model includes input
Layer, hidden layer, output layer, input layer are the pretreated pictures of input, and hidden layer is used to calculate the feature of input picture, output layer
It is to export whether the video includes abnormal scene by the calculating feature of hidden layer.Trained process is.By normal video mark
Being denoted as 0 abnormal video marker is 1, and abnormal video and normal video are then inputted training system simultaneously, pass through data
The calculating of collection pretreatment and training pattern, differentiating video is anomalous video or normal video.Above step is repeated, when being
The accuracy that system is differentiated reaches 90% or more deconditioning, preservation model.After having established model, by Model transfer to server
Data set, is changed into the video of video camera, moving model, whether the video for detecting video camera has abnormal situation by end.
Referring to Fig. 2, Fig. 2 is that the embodiment of the present invention provides a kind of flow diagram of video monitoring method.Such as Fig. 2 institute
Show, video monitoring method S200 includes:
S21, when detecting abnormal picture image by the video data that target video camera is shot, predicted anomaly picture image
The following motion track of middle target object；
In the present embodiment, monitoring server detects abnormal picture image by the video data that target video camera is shot
When, video detection Exception Model is obtained first.Secondly, monitoring server judges picture in the video data of target video camera shooting
Whether image matches video detection Exception Model；Again, if matching, monitoring server is using picture image as abnormal picture figure
Picture；If not matching, monitoring server is using picture image as normal pictures image.
In the present embodiment, video detection Exception Model can be constructed in advance.For example, firstly, monitoring server obtains instruction
Practice sets of video data, training video data set includes the video data of a variety of abnormal scenes.Secondly, monitoring server is to a variety of different
The video data of normal scene is pre-processed.Again, monitoring server handles pretreated video data by convolution algorithm,
Establish video detection Exception Model.
When monitoring server detects abnormal picture image, monitoring server analyzes abnormal draw according to image analysis algorithm
Face image extracts target object from abnormal picture image, for example, extracting violation doubling or vehicle that is interspersed or turning around.
Secondly, in monitoring server predicted anomaly picture image target object the following motion track, the following motion track be relative to
Current monitor time, target object can mobile directions in follow-up time.For example, firstly, monitoring server determines exception
Geographical location locating for target object in picture image.Secondly, monitoring server obtains geographical location locating for target object
Topographic map.Again, monitoring server predicts that the following of target object moves according to the current moving direction and topographic map of target object
Dynamic rail mark, the reverse driving for example, target vehicle turns around in one-way road, until original monitoring area may be travelled out and converted
To the monitoring area by another monitoring server management.
S22, judge whether the following motion track of target object is detached from the monitoring area range of monitoring server；
S23, according to judging result, monitoring objective object.
In the present embodiment, if the following motion track of target object is detached from the monitoring area range of monitoring server, prison
Control server determines other video cameras of the following motion track of coverage coverage goal object；Secondly, monitoring server is sentenced
Whether other video cameras that break with target video camera connect same monitoring server；If so, calling the video of other video camera shootings
Data.If it is not, calling the video data for the other monitoring servers connecting with other video cameras, wherein other monitoring servers
Video data transmit from other video cameras to other monitoring servers.Therefore, user can be uninterruptedly continuously to target
Object implements overall monitor.
If the following motion track of target object without departing from the monitoring area range of the monitoring server, continues to monitor mesh
Mark object.
To sum up, on the one hand, it can automatically detect in video with the presence or absence of abnormal picture image, implement video prison with this
Control, fully and effectively monitors so as to perform to make target object in abnormal picture image in advance.On the other hand, may be used also
Fully and effectively monitored to be further ensured that and make by the following motion track implementing monitoring of prediction target object.
In some embodiments, when monitoring server calls the video data of other video camera shootings, monitoring server is true
The target geographic position that the following motion track of object that sets the goal is related to is located at other video cameras of target geographic position to management
Other monitoring servers send video call request other taken the photograph so that other monitoring servers are returned according to video call request
The video data of camera shooting.Then, monitoring server can check that other video cameras of other monitoring server management are clapped
The video data taken the photograph.
In some embodiments, movement of the monitoring server according to target object, the holder adjustment of control target video camera
Pick-up lens is followed by the movement of target object and moves.In some embodiments, when target Camera location target object, prison
The walking path of target object can be drawn and be saved to control server, when so as to subsequent analysis target object, provide convenience.
Since target object is the object that monitoring server is paid close attention to, in order to which the later period can analyze mesh by high-definition image
Object is marked, monitoring server can amplify the video pictures comprising target object, to obtain the more details picture of target object.
Alternatively, monitoring server can also be reduced comprising target object in order to which the later period can restore the ambient enviroment of target object comprehensively
Video pictures, to obtain the bigger field range comprising target object as far as possible.
In general, the more worth emphasis of object when some abnormal conditions occurs in some video scene, in the video scene
Concern, such as steal, fight, in crowd fighting, shriek, sobs, smog or the exception scene such as noisy plundering, trailing
Object merits special attention.Therefore, in some embodiments, monitoring server controls target Camera location target object
When, firstly, whether monitoring server judgement matches default video detection Exception Model comprising the target video frame of target object；If
Matching controls target object described in target Camera location using target video frame as tracking initiation point.If not matching, continue to sentence
Whether the disconnected next frame target video frame comprising target object matches default video detection Exception Model.
In some embodiments, target object is personage, and the quantity of video camera is at least two, and different cameras can be never
With angle shot personage.Monitoring server controls target Camera location target object using target video frame as tracking initiation point
When, monitoring server first obtains the character image of target video camera shooting personage using target video frame as tracking initiation point.
Secondly, monitoring server judge character image whether be personage direct picture, direct picture includes the people of personage
Face image.For example, first trails second, wait for an opportunity the handbag of pickpocket's second, the camera supervised trailing action behavior to first, and will include
The video data of the trailing action behavior of first is sent to monitoring server, and monitoring server detects the trailing action behavior of first,
And determine that first is target person.Monitoring server judges video data further according to the character image of image analysis algorithm analysis first
With the presence or absence of with the associated human face characteristic point of target person, and if it exists, then think video data include target person front elevation
Picture；If not existing, then it is assumed that video data does not include the direct picture of target person, and the video data only includes target person
The back side image of object.For example, accepting above-mentioned example, if monitoring server detects the facial image of first in video data, recognize
The direct picture of first is taken for target video camera.If monitoring server does not detect the facial image of first in video data,
Think that target video camera takes the back side image of first.
Again, if the direct picture of personage, monitoring server controls target Camera location personage；If it is not, monitoring clothes
Business device detects that the additional video camera being oppositely arranged with target video camera, the outer video camera of quota shoot the direct picture of personage,
And tracking person.For example, when monitoring server detects video data and do not include the direct picture of target person, monitoring service
Device determines the current geographic position of target person.
Secondly, current geographic position of the monitoring server according to target person, the current position of detection and coverage goal personage
It manages all additional video cameras of position and determines the installation geographical location of all additional video cameras, and from all additional video cameras
It installs and determines the additional video camera opposite with the installation geographical location of target video camera in geographical location.
Again, the monitoring server control additional Camera location personage opposite with the installation geographical location of target video camera
And shoot the direct picture of personage.
In fact, some malignant event time of origins major parts are weak equal dark local in light, in order to prevent illegal person,
Strive for obtaining illegal person high definition facial image, in some embodiments, monitoring server detects opposite with target video camera
When the additional video camera being arranged, firstly, monitoring server obtains the intensity of illumination in predeterminable area, for example, being set to preset areas
Optical sensor in domain acquires intensity of illumination, and intensity of illumination is transmitted to monitoring server.
Secondly, monitoring server judges whether intensity of illumination is greater than preset strength threshold value, if more than obtaining and imaging with target
The minimal illumination value for all additional video cameras that machine is oppositely arranged, traverses out most from the minimal illumination value of all additional video cameras
Low-light (level) is worth video camera of the minimum additional video camera as the direct picture for tracking and shooting personage, then, monitoring server
Just personage's direct picture of high definition is got as much as possible.If being less than, detect to be oppositely arranged with target video camera is additionally taken the photograph
Camera.
In this manner, personage's direct picture of high definition can be got as much as possible, effectively regarded to realize
Frequency monitors.
It should be noted that not necessarily there is centainly successive between above steps in above-mentioned each embodiment
Sequentially, those of ordinary skill in the art, according to an embodiment of the present invention to describe to be appreciated that in different embodiments, above-mentioned each step
Suddenly there can be the different sequences that executes, also i.e., it is possible to execute parallel, execution etc. can also be exchanged.
As the another aspect of the embodiment of the present invention, the embodiment of the present invention provides a kind of video monitoring apparatus.The present invention is real
The video monitoring apparatus for applying example can be used as one of SFU software functional unit, and video monitoring apparatus includes some instructions, if should
Dry instruction is stored in memory, and the accessible memory of processor, call instruction is executed, to complete above-mentioned video prison
Prosecutor method.
Referring to Fig. 3, video monitoring apparatus 300 includes: prediction module 31, judgment module 32 and monitoring module 33.
Prediction module 31 is for predicting institute when detecting abnormal picture image by the video data that target video camera is shot
State the following motion track of target object in abnormal picture image；
Judgment module 32 is for judging whether the following motion track of the target object is detached from the monitoring server
Monitoring area range；
Monitoring module 33 is used to monitor the target object according to judging result.
To sum up, on the one hand, it can automatically detect in video with the presence or absence of abnormal picture image, implement video prison with this
Control, fully and effectively monitors so as to perform to make target object in abnormal picture image in advance.On the other hand, may be used also
Fully and effectively monitored to be further ensured that and make by the following motion track implementing monitoring of prediction target object.
In some embodiments, the monitoring module 33 is specifically used for: if the following motion track of the target object is de-
Monitoring area range from the monitoring server determines that coverage covers its of the following motion track of the target object
Its video camera；Judge whether other video cameras with the target video camera connect same monitoring server；If so, calling institute
State the video data of other video camera shootings；If it is not, calling the view for the other monitoring servers connecting with other video cameras
Frequency evidence, wherein the video data of other monitoring servers is from other video cameras to other monitoring servers
Transmission；If the following motion track of the target object continues to supervise without departing from the monitoring area range of the monitoring server
Control the target object.
It should be noted that above-mentioned security protection data uploading device can be performed in security protection data provided by the embodiment of the present invention
Transmission method has the corresponding functional module of execution method and beneficial effect.It is not detailed in security protection data uploading device embodiment
The technical detail of description, reference can be made to security protection data uploading method provided by the embodiment of the present invention.
As the another aspect of the embodiment of the present invention, the embodiment of the present invention provides a kind of monitoring server.Such as Fig. 4 institute
Show, which includes: one or more processors 41 and memory 42.Wherein, with a processor in Fig. 4
For 41.
Processor 41 can be connected with memory 42 by bus or other modes, to be connected as by bus in Fig. 4
Example.
Memory 42 is used as a kind of non-volatile computer readable storage medium storing program for executing, can be used for storing non-volatile software journey
Sequence, non-volatile computer executable program and module, such as the corresponding program of video monitoring method in the embodiment of the present invention
Instruction/module.Non-volatile software program, instruction and the module that processor 41 is stored in memory 42 by operation, from
And execute the various function application and data processing of video monitoring apparatus, that is, realize above method embodiment video monitoring method
And the function of the modules of above-mentioned apparatus embodiment.
Memory 42 may include high-speed random access memory, can also include nonvolatile memory, for example, at least
One disk memory, flush memory device or other non-volatile solid state memory parts.In some embodiments, memory 42
Optional includes the memory remotely located relative to processor 41, these remote memories can pass through network connection to processor
41.The example of above-mentioned network includes but is not limited to internet, intranet, local area network, mobile radio communication and combinations thereof.
Described program instruction/module is stored in the memory 42, is held when by one or more of processors 41
When row, the video monitoring method in above-mentioned any means embodiment is executed, for example, executing each step of Fig. 2 described above；?
The function of modules described in attached drawing 3 can be achieved.
The embodiment of the invention also provides a kind of nonvolatile computer storage media, the computer storage medium storage
There are computer executable instructions, which is executed by one or more processors, such as at one in Fig. 4
Device 41 is managed, may make said one or multiple processors that the video monitoring method in above-mentioned any means embodiment, example can be performed
Such as, the video monitoring method in above-mentioned any means embodiment is executed, execution described above is described above to hold for example, executing
Row each step shown in Fig. 2 described above；It can also realize the function of modules described in attached drawing 3.
Device or apparatus embodiments described above is only schematical, wherein it is described as illustrated by the separation member
Unit module may or may not be physically separated, and the component shown as modular unit can be or can also
Not to be physical unit, it can it is in one place, or may be distributed on multiple network module units.It can basis
It is actual to need that some or all of the modules therein is selected to achieve the purpose of the solution of this embodiment.
Through the above description of the embodiments, those skilled in the art can be understood that each embodiment can
It is realized by the mode of software plus general hardware platform, naturally it is also possible to pass through hardware.Based on this understanding, above-mentioned technology
Scheme substantially in other words can be embodied in the form of software products the part that the relevant technologies contribute, the computer
Software product may be stored in a computer readable storage medium, such as ROM/RAM, magnetic disk, CD, including some instructions are with directly
To computer equipment (can be personal computer, server or the network equipment etc.) execute each embodiment or
Method described in certain parts of embodiment.
Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；At this
It under the thinking of invention, can also be combined between the technical characteristic in above embodiments or different embodiment, step can be with
It is realized with random order, and there are many other variations of different aspect present invention as described above, for simplicity, they do not have
Have and is provided in details；Although the present invention is described in detail referring to the foregoing embodiments, the ordinary skill people of this field
Member is it is understood that it is still possible to modify the technical solutions described in the foregoing embodiments, or to part of skill
Art feature is equivalently replaced；And these are modified or replaceed, each reality of the application that it does not separate the essence of the corresponding technical solution
Apply the range of a technical solution.
Claims (10)
1. a kind of video monitoring method, which is characterized in that the described method includes:
When detecting abnormal picture image by the video data that target video camera is shot, mesh in the abnormal picture image is predicted
Mark the following motion track of object；
Judge whether the following motion track of the target object is detached from the monitoring area range of the monitoring server；
According to judging result, the target object is monitored.
2. being wrapped the method according to claim 1, wherein described monitor the target object according to judging result
It includes:
If the following motion track of the target object is detached from the monitoring area range of the monitoring server, coverage is determined
Cover other video cameras of the following motion track of the target object；
Judge whether other video cameras with the target video camera connect same monitoring server；
If so, calling the video data of other video camera shootings；
If it is not, calling the video data for the other monitoring servers connecting with other video cameras, wherein other monitoring
What the video data of server was transmitted from other video cameras to other monitoring servers；
If the following motion track of the target object without departing from the monitoring area range of the monitoring server, continues to monitor institute
State target object.
3. according to the method described in claim 2, it is characterized in that, the video counts for calling other video camera shootings
According to, comprising:
Determine the target geographic position that the following motion track of the target object is related to；
The other monitoring servers for being located at other video cameras of the target geographic position to management send video call request, with
Other monitoring servers are made to return to the video data of other video camera shootings according to the video call request.
4. method according to any one of claims 1 to 3, which is characterized in that the view shot by target video camera
Frequency evidence detects abnormal picture image, comprising:
Obtain video detection Exception Model；
Judge whether picture image matches the video detection Exception Model in the video data of the target video camera shooting；
If matching, using the picture image as abnormal picture image；
If not matching, using the picture image as normal pictures image.
5. according to the method described in claim 4, it is characterized in that, the method also includes:
Training video data set is obtained, the training video data set includes the video data of a variety of abnormal scenes；
The video data of a variety of abnormal scenes is pre-processed；
Pretreated video data is handled by convolution algorithm, establishes the video detection Exception Model.
6. method according to any one of claims 1 to 3, which is characterized in that in the prediction abnormal picture image
The following motion track of target object, comprising:
Determine geographical location locating for target object in the abnormal picture image；
Obtain the topographic map in geographical location locating for the target object；
According to the current moving direction of the target object and the topographic map, the following moving rail of the target object is predicted
Mark.
7. a kind of video monitoring apparatus, which is characterized in that described device includes:
Prediction module when the video data for being shot by target video camera detects abnormal picture image, is predicted described different
The following motion track of target object in normal picture image；
Judgment module, for judging whether the following motion track of the target object is detached from the monitored space of the monitoring server
Domain range；
Monitoring module, for monitoring the target object according to judging result.
8. device according to claim 7, which is characterized in that the monitoring module is specifically used for:
If the following motion track of the target object is detached from the monitoring area range of the monitoring server, coverage is determined
Cover other video cameras of the following motion track of the target object；
Judge whether other video cameras with the target video camera connect same monitoring server；
If so, calling the video data of other video camera shootings；
If it is not, calling the video data for the other monitoring servers connecting with other video cameras, wherein other monitoring
What the video data of server was transmitted from other video cameras to other monitoring servers；
If the following motion track of the target object without departing from the monitoring area range of the monitoring server, continues to monitor institute
State target object.
9. a kind of monitoring server characterized by comprising
At least one processor；And
The memory being connect at least one described processor communication；Wherein, be stored with can be by described at least one for the memory
The instruction that a processor executes, described instruction is executed by least one described processor, so that at least one described processor energy
It is enough in execution such as video monitoring method as claimed in any one of claims 1 to 6.
10. a kind of video monitoring system characterized by comprising
Several video cameras；
Monitoring server as claimed in claim 9, the monitoring server and the video camera communicate.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811120075.8A CN109040709B (en) | 2018-09-21 | 2018-09-21 | Video monitoring method and device, monitoring server and video monitoring system |
| PCT/CN2019/103766 WO2020057346A1 (en) | 2018-09-21 | 2019-08-30 | Video monitoring method and apparatus, monitoring server and video monitoring system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811120075.8A CN109040709B (en) | 2018-09-21 | 2018-09-21 | Video monitoring method and device, monitoring server and video monitoring system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109040709A true CN109040709A (en) | 2018-12-18 |
| CN109040709B CN109040709B (en) | 2020-12-08 |
Family
ID=64618457
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811120075.8A Active CN109040709B (en) | 2018-09-21 | 2018-09-21 | Video monitoring method and device, monitoring server and video monitoring system |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN109040709B (en) |
| WO (1) | WO2020057346A1 (en) |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109685012A (en) * | 2018-12-25 | 2019-04-26 | 秒针信息技术有限公司 | The video monitoring method and device of biology |
| CN109822570A (en) * | 2019-01-31 | 2019-05-31 | 秒针信息技术有限公司 | The monitoring method and device of mechanical arm |
| CN110022379A (en) * | 2019-04-23 | 2019-07-16 | 翔创科技（北京）有限公司 | A kind of livestock monitoring system and method |
| CN110244611A (en) * | 2019-06-06 | 2019-09-17 | 北京迈格威科技有限公司 | A kind of pet monitoring method and device |
| CN110309735A (en) * | 2019-06-14 | 2019-10-08 | 平安科技（深圳）有限公司 | Exception detecting method, device, server and storage medium |
| CN110446014A (en) * | 2019-08-26 | 2019-11-12 | 深圳前海达闼云端智能科技有限公司 | Monitoring method, monitoring equipment and computer readable storage medium |
| WO2020057346A1 (en) * | 2018-09-21 | 2020-03-26 | 深圳市九洲电器有限公司 | Video monitoring method and apparatus, monitoring server and video monitoring system |
| CN110928305A (en) * | 2019-12-03 | 2020-03-27 | 中国铁道科学研究院集团有限公司电子计算技术研究所 | Patrol method and system for railway passenger station patrol robot |
| CN111028473A (en) * | 2019-12-20 | 2020-04-17 | 博瑞资(重庆)教育科技有限公司 | Campus safety monitoring linkage identification system |
| CN111046822A (en) * | 2019-12-19 | 2020-04-21 | 山东财经大学 | Large vehicle anti-theft method based on artificial intelligence video identification |
| CN111669540A (en) * | 2019-03-07 | 2020-09-15 | 上海思桂信息技术有限公司 | Monitoring system and method based on AI technology |
| CN111898486A (en) * | 2020-07-14 | 2020-11-06 | 浙江大华技术股份有限公司 | Method and device for detecting abnormity of monitoring picture and storage medium |
| CN111970482A (en) * | 2020-07-08 | 2020-11-20 | 广东电网有限责任公司 | Monitoring device and system for outer broken scene |
| CN114584746A (en) * | 2022-04-29 | 2022-06-03 | 深圳市边海物联科技有限公司 | Security monitoring system and security monitoring method |
| CN115052110A (en) * | 2022-08-16 | 2022-09-13 | 中保卫士保安服务有限公司 | Security method, security system and computer readable storage medium |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020152557A1 (en) * | 1997-08-25 | 2002-10-24 | David Elberbaum | Apparatus for identifying the scene location viewed via remotely operated television camera |
| CN1396488A (en) * | 2001-07-09 | 2003-02-12 | 富士胶片株式会社 | Camera device with flasher |
| CN1426564A (en) * | 2000-12-28 | 2003-06-25 | 高桥淳 | Remote internet technical guidance/education distribution system using practitioner's vision, and guidance system using communication network |
| EP1363810A2 (en) * | 2001-01-23 | 2003-11-26 | Donnelly Corporation | Improved vehicular lighting system |
| CN1615640A (en) * | 2001-11-15 | 2005-05-11 | J·M·杰克·金 | Dual camera surveillance and control system |
| JP2005142683A (en) * | 2003-11-04 | 2005-06-02 | Matsushita Electric Ind Co Ltd | Apparatus and method for camera control |
| CN100369464C (en) * | 2003-09-17 | 2008-02-13 | 松下电器产业株式会社 | Surveillance video camera |
| CN101755190A (en) * | 2008-05-19 | 2010-06-23 | 松下电器产业株式会社 | Calibration method, calibration device, and calibration system having the device |
| CN102480593A (en) * | 2010-11-25 | 2012-05-30 | 杭州华三通信技术有限公司 | Double-lens video camera switching method and device |
| CN103329518A (en) * | 2011-01-11 | 2013-09-25 | 松下电器产业株式会社 | Image capturing system, camera control device for use therein, image capturing method, camera control method, and computer program |
| CN104079885A (en) * | 2014-07-07 | 2014-10-01 | 广州美电贝尔电业科技有限公司 | Nobody-monitored and linkage-tracked network camera shooting method and device |
| CN104103030A (en) * | 2013-04-08 | 2014-10-15 | 佳能株式会社 | Image analysis method, camera apparatus, control apparatus and control method |
| CN104539909A (en) * | 2015-01-15 | 2015-04-22 | 安徽大学 | Video monitoring method and video monitoring server |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104239851B (en) * | 2014-07-25 | 2018-05-01 | 重庆科技学院 | The intelligent residential district cruising inspection system and its control method of Behavior-based control analysis |
| JP6465600B2 (en) * | 2014-09-19 | 2019-02-06 | キヤノン株式会社 | Video processing apparatus and video processing method |
| CN106709436B (en) * | 2016-12-08 | 2020-04-24 | 华中师范大学 | Track traffic panoramic monitoring-oriented cross-camera suspicious pedestrian target tracking system |
| CN107644206A (en) * | 2017-09-20 | 2018-01-30 | 深圳市晟达机械设计有限公司 | A kind of road abnormal behaviour action detection device |
| CN108055501A (en) * | 2017-11-22 | 2018-05-18 | 天津市亚安科技有限公司 | A kind of target detection and the video monitoring system and method for tracking |
| CN108052882A (en) * | 2017-11-30 | 2018-05-18 | 广东云储物联视界科技有限公司 | A kind of operating method of intelligent safety defense monitoring system |
| CN109040709B (en) * | 2018-09-21 | 2020-12-08 | 深圳市九洲电器有限公司 | Video monitoring method and device, monitoring server and video monitoring system |
-
2018
- 2018-09-21 CN CN201811120075.8A patent/CN109040709B/en active Active
-
2019
- 2019-08-30 WO PCT/CN2019/103766 patent/WO2020057346A1/en active Application Filing
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020152557A1 (en) * | 1997-08-25 | 2002-10-24 | David Elberbaum | Apparatus for identifying the scene location viewed via remotely operated television camera |
| CN1426564A (en) * | 2000-12-28 | 2003-06-25 | 高桥淳 | Remote internet technical guidance/education distribution system using practitioner's vision, and guidance system using communication network |
| EP1363810A2 (en) * | 2001-01-23 | 2003-11-26 | Donnelly Corporation | Improved vehicular lighting system |
| CN1396488A (en) * | 2001-07-09 | 2003-02-12 | 富士胶片株式会社 | Camera device with flasher |
| CN1279751C (en) * | 2001-11-15 | 2006-10-11 | J·M·杰克·金 | Dual camera surveillance and control system |
| CN1615640A (en) * | 2001-11-15 | 2005-05-11 | J·M·杰克·金 | Dual camera surveillance and control system |
| CN100369464C (en) * | 2003-09-17 | 2008-02-13 | 松下电器产业株式会社 | Surveillance video camera |
| JP2005142683A (en) * | 2003-11-04 | 2005-06-02 | Matsushita Electric Ind Co Ltd | Apparatus and method for camera control |
| CN101755190A (en) * | 2008-05-19 | 2010-06-23 | 松下电器产业株式会社 | Calibration method, calibration device, and calibration system having the device |
| CN102480593A (en) * | 2010-11-25 | 2012-05-30 | 杭州华三通信技术有限公司 | Double-lens video camera switching method and device |
| CN103329518A (en) * | 2011-01-11 | 2013-09-25 | 松下电器产业株式会社 | Image capturing system, camera control device for use therein, image capturing method, camera control method, and computer program |
| CN104103030A (en) * | 2013-04-08 | 2014-10-15 | 佳能株式会社 | Image analysis method, camera apparatus, control apparatus and control method |
| CN104079885A (en) * | 2014-07-07 | 2014-10-01 | 广州美电贝尔电业科技有限公司 | Nobody-monitored and linkage-tracked network camera shooting method and device |
| CN104539909A (en) * | 2015-01-15 | 2015-04-22 | 安徽大学 | Video monitoring method and video monitoring server |
Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020057346A1 (en) * | 2018-09-21 | 2020-03-26 | 深圳市九洲电器有限公司 | Video monitoring method and apparatus, monitoring server and video monitoring system |
| CN109685012A (en) * | 2018-12-25 | 2019-04-26 | 秒针信息技术有限公司 | The video monitoring method and device of biology |
| CN109822570A (en) * | 2019-01-31 | 2019-05-31 | 秒针信息技术有限公司 | The monitoring method and device of mechanical arm |
| CN111669540A (en) * | 2019-03-07 | 2020-09-15 | 上海思桂信息技术有限公司 | Monitoring system and method based on AI technology |
| CN110022379A (en) * | 2019-04-23 | 2019-07-16 | 翔创科技（北京）有限公司 | A kind of livestock monitoring system and method |
| CN110244611A (en) * | 2019-06-06 | 2019-09-17 | 北京迈格威科技有限公司 | A kind of pet monitoring method and device |
| CN110309735A (en) * | 2019-06-14 | 2019-10-08 | 平安科技（深圳）有限公司 | Exception detecting method, device, server and storage medium |
| CN110446014A (en) * | 2019-08-26 | 2019-11-12 | 深圳前海达闼云端智能科技有限公司 | Monitoring method, monitoring equipment and computer readable storage medium |
| CN110928305B (en) * | 2019-12-03 | 2023-08-18 | 中国铁道科学研究院集团有限公司电子计算技术研究所 | Patrol method and system for patrol robot of railway passenger station |
| CN110928305A (en) * | 2019-12-03 | 2020-03-27 | 中国铁道科学研究院集团有限公司电子计算技术研究所 | Patrol method and system for railway passenger station patrol robot |
| CN111046822A (en) * | 2019-12-19 | 2020-04-21 | 山东财经大学 | Large vehicle anti-theft method based on artificial intelligence video identification |
| CN111028473A (en) * | 2019-12-20 | 2020-04-17 | 博瑞资(重庆)教育科技有限公司 | Campus safety monitoring linkage identification system |
| CN111970482A (en) * | 2020-07-08 | 2020-11-20 | 广东电网有限责任公司 | Monitoring device and system for outer broken scene |
| CN111898486A (en) * | 2020-07-14 | 2020-11-06 | 浙江大华技术股份有限公司 | Method and device for detecting abnormity of monitoring picture and storage medium |
| CN111898486B (en) * | 2020-07-14 | 2024-05-10 | 浙江大华技术股份有限公司 | Monitoring picture abnormality detection method, device and storage medium |
| CN114584746A (en) * | 2022-04-29 | 2022-06-03 | 深圳市边海物联科技有限公司 | Security monitoring system and security monitoring method |
| CN115052110A (en) * | 2022-08-16 | 2022-09-13 | 中保卫士保安服务有限公司 | Security method, security system and computer readable storage medium |
| CN115052110B (en) * | 2022-08-16 | 2022-11-18 | 中保卫士保安服务有限公司 | Security method, security system and computer readable storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2020057346A1 (en) | 2020-03-26 |
| CN109040709B (en) | 2020-12-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109040709A (en) | Video monitoring method and device, monitoring server and video monitoring system | |
| CN109241933A (en) | Video linkage monitoring method, monitoring server, video linkage monitoring system | |
| Elharrouss et al. | A review of video surveillance systems | |
| CN109376601A (en) | Object tracking methods, monitoring server based on clipping the ball, video monitoring system | |
| US10614311B2 (en) | Automatic extraction of secondary video streams | |
| CN105894702B (en) | A kind of intrusion detection warning system and its detection method based on multiple-camera data fusion | |
| Wheeler et al. | Face recognition at a distance system for surveillance applications | |
| US7733369B2 (en) | View handling in video surveillance systems | |
| CN104040601B (en) | Video monitor based on cloud management system | |
| CN101119482B (en) | Overall view monitoring method and apparatus | |
| US8848053B2 (en) | Automatic extraction of secondary video streams | |
| CN111242025B (en) | Real-time action monitoring method based on YOLO | |
| CN111291633A (en) | Real-time pedestrian re-identification method and device | |
| CN109684494A (en) | A kind of scenic spot looking-for-person method, system and cloud server | |
| WO2021068553A1 (en) | Monitoring method, apparatus and device | |
| CN106385561A (en) | Public place video monitoring platform | |
| KR101290782B1 (en) | System and method for Multiple PTZ Camera Control Based on Intelligent Multi-Object Tracking Algorithm | |
| CN201142737Y (en) | Front end monitoring apparatus for IP network video monitoring system | |
| JP2009060261A (en) | Video monitoring system | |
| CN111711796A (en) | Intelligent human shape detection system | |
| CN113660455B (en) | Method, system and terminal for fall detection based on DVS data | |
| Fleck et al. | Privacy sensitive surveillance for assisted living–a smart camera approach | |
| Nishanthini et al. | Smart Video Surveillance system and alert with image capturing using android smart phones | |
| JP4445309B2 (en) | Monitoring device, monitoring system, motion detection device, and photographing device | |
| US20240212349A1 (en) | Multipurpose visual & auditory intelligent observer system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |