CN107948586B - Trans-regional moving target detecting method and device based on video-splicing - Google Patents
Trans-regional moving target detecting method and device based on video-splicing Download PDFInfo
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- 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
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
- G06T7/285—Analysis of motion using a sequence of stereo image pairs
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- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
- G06T7/33—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
- G06T7/337—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods involving reference images or patches
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
- G06T2207/10021—Stereoscopic video; Stereoscopic image sequence
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Abstract
The invention discloses a kind of trans-regional moving target detecting method and device based on video-splicing, which comprises while reading input of the multichannel live video stream as video flowing；The multichannel live video stream is spliced, splicing video flowing is obtained and is stored in splicing video stream data area；The splicing video flowing for reading the data from splicing video stream data area simultaneously, carries out moving object detection.The present invention is handled splicing video flowing using multi-thread mechanism, improves moving object detection efficiency.
Description
Technical field
The present invention relates to monitor video process field more particularly to a kind of trans-regional moving target inspections based on video-splicing
Survey method and apparatus.
Background technique
During smart city and increasingly developed artificial intelligence, based on the intellectual analysis of monitor video in people day
Often played an increasingly important role in life.And moving object detection is the basis of monitor video intellectual analysis, video intelligence
Can analysis in many functions have relied on moving object detection as a result, for example, crowd density statistics, intelligent barrier avoiding, mesh
Mark is retrieved, is driven in the wrong direction, swarming into and break, hover, so the moving object detection based on monitor video has stronger researching value.
But the moving object detection of monitoring field is all based on single monitoring area (i.e. the region of single camera monitoring) Lai Shixian at present,
To which the visual field of the intellectual analysis to video is also limited to single monitoring area, the visual field of moving object detection can not be expanded.
With the continuous development of computer vision technique, current video-splicing technology and its application are very mature,
Image mosaic is exactly that several single pictures with certain overlapping region are synthesized the picture of a large scene, to expand
The scene visual field of single picture and content.And in field of video monitoring, in order to rapidly to the content in video carry out identification and
Analysis has very high requirement for the splicing efficiency of different video flowings.
Meanwhile during the application of computer vision technique is constantly expanded, for the result of moving object detection
There is the requirement of high-accuracy, high time efficiency.And the moving object detection algorithm based on traditional machine learning is unable to satisfy
The demand of detection.
Therefore, the motion estimate efficiency across video area how is improved, is that those skilled in the art urgently solve at present
Certainly the technical issues of.
Summary of the invention
To overcome above-mentioned the deficiencies in the prior art, the present invention provides a kind of cross-domain area's moving target based on video-splicing
Detection method can realize the video-splicing based on more monitoring areas to expand monitoring visual field, herein using video-splicing technology
On the basis of using depth learning technology realize moving object detection, reach the high-accuracy of moving object detection, high time efficiency
Requirement, eliminate the limitation of single monitoring area target detection, the regional vision of moving object detection expanded, to realize
Trans-regional moving object detection.
To achieve the above object, the present invention adopts the following technical scheme:
A kind of trans-regional moving target detecting method based on video-splicing, comprising the following steps:
Input of the multichannel live video stream as video flowing is read simultaneously；
The multichannel live video stream is spliced, splicing video flowing is obtained and is stored in splicing video stream data area；
The splicing video flowing for reading the data from splicing video stream data area simultaneously, carries out moving object detection.
Further, after the method carries out moving object detection further include: the moving target that will test is in video flowing
In mark and show in real time.
Further, multichannel live video stream is carried out splicing includes:
The multi-path video stream of reading is registrated, registration parameter is calculated and is saved；
For the multi-path video stream of subsequent reading, registration parameter is read, is merged based on the registration parameter.
Further, the multi-path video stream of described pair of reading, which be registrated, includes:
(1) feature extraction is carried out to the multi-path video stream of reading；
(2) feature of extraction is matched；
(3) according to the matching result of feature, camera parameter and homography matrix are calculated；
(4) image coordinate system of different video stream is mapped to by the same third-party spherical coordinate according to homography matrix
System；
(5) it is mapped in the same coordinate system, is calculated between different video stream according to different video stream homography conversion
Overlapping region；
(6) splicing seams between different video stream are found in overlapping region dynamic using max-flow min-cut algorithm, calculated
Subsequent registration parameter simultaneously saves.
Further, include: to the multi-path video stream fusion of subsequent reading
Registration parameter is read, homography conversion is carried out to the video flowing of subsequent reading；
The fusion of video flowing is carried out based on the registration parameter.
Further, the moving object detection includes:
Target in monitoring video frame is labeled, as trained and test data set；
Based on trained and test data set training moving object detection model；
The splicing video flowing for reading splicing video stream data area in real time carries out moving object detection.
Further, the mark includes the coordinate and classification information of label target.
Further, the moving object detection model is based on DarkNet frame application yolo network model.
Second purpose according to the present invention, the trans-regional moving target inspection based on video-splicing that the present invention also provides a kind of
Device is surveyed, including memory, processor (including CPU and GPU) and stores the meter that can be run on a memory and on a processor
Calculation machine program, the processor realize the trans-regional moving object detection side based on video-splicing when executing described program
Method.
Third purpose according to the present invention, the present invention also provides a kind of computer readable storage mediums, are stored thereon with
Computer program executes the trans-regional moving object detection side based on video-splicing when the program is executed by processor
Method.
Beneficial effects of the present invention
1, the present invention is handled splicing video flowing using multi-thread mechanism, in video stream splicing and moving object detection
Between establish a splicing video stream data area be responsible for storage splicing video flowing, for splice video stream data area, video-splicing
Process is responsible for for the video flowing after having spliced being stored in the data field, and detection process of moving target is responsible for reading the splicing view of the data
Frequency flows, so that video stream splicing and moving object detection carry out simultaneously parallel, is being not pipeline system but parallel type, is improving
The operational efficiency of algorithm entirety.
2, the present invention is saved into file calculating registration parameter between different video stream in video-splicing first, then right
In subsequent video stream, reads the registration parameter and realize fusion, realize the real-time of video stream splicing.
3, the present invention completes moving target in moving object detection part, the middle yolo algorithm that depth learning technology is utilized
Detection, relative to the target detection of traditional machine learning algorithm, is all greatly improved in speed and accuracy rate.
Detailed description of the invention
The accompanying drawings constituting a part of this application is used to provide further understanding of the present application, and the application's shows
Meaning property embodiment and its explanation are not constituted an undue limitation on the present application for explaining the application.
Fig. 1 is a kind of trans-regional moving target detecting method overall flow schematic diagram based on video-splicing of the present invention；
Fig. 2 is the whole flow diagram of video-splicing；
Fig. 3 is video stream splicing process in cross-domain area's moving target detecting method based on video-splicing a kind of in the present invention
Schematic diagram.
Specific embodiment
It is noted that following detailed description is all illustrative, it is intended to provide further instruction to the application.Unless another
It indicates, all technical and scientific terms used herein has usual with the application person of an ordinary skill in the technical field
The identical meanings of understanding.
It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to restricted root
According to the illustrative embodiments of the application.As used herein, unless the context clearly indicates otherwise, otherwise singular
Also it is intended to include plural form, additionally, it should be understood that, when in the present specification using term "comprising" and/or " packet
Include " when, indicate existing characteristics, step, operation, device, component and/or their combination.
In the absence of conflict, the features in the embodiments and the embodiments of the present application can be combined with each other.
Embodiment one
Present embodiment discloses a kind of trans-regional moving target detecting method based on video-splicing, overall structure and process
Figure is as shown in Figure 1 comprising two large divisions: video-splicing, moving object detection.
Video flowing input
By video integration platform, real-time video stream data is read from the acquisition of video access service device, while reading more
Input of the real-time video flowing in road as video flowing.
Real-time video splicing
Image mosaic is the picture for several single pictures with certain overlapping region being synthesized a large scene, from
And expand the scene visual field and the content of picture.The whole flow chart of video-splicing is as shown in Fig. 2, include feature extraction, feature
Matching, homography conversion, finds splicing seams, image mosaic at camera parameter estimation.
Current splicing is all based on video frame to realize, algorithm entire for the splicing of plurality of pictures is more complicated
, time complexity is very high.It is to need the high time for the moving object detection in the monitoring field video intelligent analysis of security protection
The requirement of efficiency, so the high time complexity of splicing is to be unable to satisfy moving object detection real-time requirement.
A kind of cross-domain area's moving target detecting method based on video-splicing of the invention, proposes one in video-splicing
The method of kind optimization makes the splicing of video flowing can satisfy real-time.The splicing of video flowing is divided into two modules by the present invention:
Registration module and splicing module, structure chart are as shown in Figure 3.
For the video stream splicing registration module in the present invention, the first frame of different video stream is read first, it is basic herein
The upper surf feature for extracting different video frame is described as subsequent feature, and surf feature generally has scale invariability and calculating
The characteristics such as speed is fast, compare and are suitble to apply in video-splicing.After the surf feature for having extracted different video frame, need to difference
The feature of video frame extraction is registrated, and to judge whether it has common characteristic point, arest neighbors and time neighbour's ratio is selected to calculate
Method carrys out processing feature matching, the distance (selecting Euclidean distance in the present invention) of arest neighbors and time neighbour's feature pair is calculated, if most
The threshold value that neighbour's feature sets Euclidean distance divided by secondary neighbour's feature to Euclidean distance less than one then judges its arest neighbors spy
Sign is to being identical characteristic point.According to the matching result of characteristic point, combining camera and image coordinate system and world coordinate system
Mapping relations calculate the parameter of camera, including Intrinsic Matrix and outer parameter matrix.
Since different video flowings is different camera shooting, so their image coordinate system is not in the same seat
In mark system, so the image coordinate system by different video stream is needed to be mapped in same third party's coordinate system.This third party
Coordinate system is typically chosen spherical coordinate or cylindrical coordinate system, selects spherical coordinate in the present invention.Utilize camera parameter
The available homography matrix of calculating, different video streaming image coordinate systems can be mapped to by homography matrix same
A spherical coordinate.The overlapping region between different video stream can be calculated by homography conversion, video-splicing is desirable
A splicing seams are found in the overlapping region of different video stream, find this splicing seams using max-flow min-cut algorithm dynamic.
After finding the splicing seams of video flowing, the Parametric registration process for input video stream is just completed, that is, is extracted
Surf feature carries out characteristic matching, camera parameter estimation, homography conversion, splicing seams searching.Registration process is exactly calculated for subsequent
Parameter (size including input video stream, homography matrix, the mask etc. of splicing seams) required for splicing, it is subsequent to splice
Journey is namely based on this registration parameter and carries out image co-registration, and the present invention presses parameter required for subsequent splicing after registration
It is written in xml document and is saved according to customized format, so that parameter calculating is once to calculate.
After registration module, splicing module does not need to repeat the whole flow process of video-splicing after reading new video flowing
, only need to read the parameter that registration module is written in xml document in the present invention, according to homography matrix parameter to access
Video flowing directly carry out homography conversion and be mapped in the same coordinate system, directly utilize more waves according to the mask parameters of splicing seams
Section (i.e. building gaussian sum laplacian pyramid) is merged, and the splicing of live video stream is completed.
Splice video flow processing
For the splicing video flowing of splicing output, moving target is carried out using yolo algorithm if directly carrying out pipeline system
Detection, it may appear that be unable to satisfy the high time efficiency of moving object detection.The present invention is using multi-thread mechanism to splicing video flowing
It is handled, a splicing video stream data area is established between video stream splicing and moving object detection and is responsible for storage splicing view
Frequency flows, and for splicing video stream data area, video-splicing is responsible for the video flowing after having spliced being stored in the data field, moving target
Detection is responsible for reading the splicing video flowing of the data, so that video stream splicing and moving object detection carry out simultaneously parallel, without
It is being pipeline system but parallel type, the efficiency of time can be improved.
Moving object detection
In video intelligent analysis, the target detection limitation based on traditional machine learning algorithm is very big, and detection is accurate
Rate is low and is easy to appear leak detection and error detection, and the time efficiency of detection is unable to satisfy real-time detection demand, and traditional machine
It is characterized in needing manually to design in device learning algorithm.A kind of cross-domain area's moving target based on video-splicing of the invention
Detection method, in moving object detection part, the middle yolo algorithm that depth learning technology is utilized completes moving object detection,
Speed and accuracy rate are all greatly improved.It initially needs to mark a large amount of target (mesh to be detected based on monitoring video frame
Mark coordinate and classification information) data set, moving object detection model is trained based on DarkNet frame application yolo network model,
Trained model is saved.
After completing detection model training process, target detection of the invention disposably initializes trained yolo detection mould
Type, the subsequent real-time splicing video flowing for reading splicing video stream data area carry out moving object detection.
Trans-regional testing result
What yolo detection model was detected on splicing video flowing detects the coordinate and class of moving target as a result, saving
Other information, and mark according to coordinate and classification information position and the classification of moving target in real time in video streaming, and real-time display.
Embodiment two
The purpose of the present embodiment is to provide a kind of computing device.
A kind of trans-regional moving object detection device based on video-splicing, including memory, processor (CPU and GPU)
And storage is on a memory and the computer program that can run on a processor, when the processor executes described program realization with
Lower step, comprising:
Step 1: while reading input of the multichannel live video stream as video flowing；
Step 2: the multichannel live video stream being spliced, splicing video flowing is obtained and is stored in splicing video fluxion
According to area；
Step 3: while the splicing video flowing of the data is read from splicing video stream data area, carry out moving object detection.
Embodiment three
The purpose of the present embodiment is to provide a kind of computer readable storage medium.
A kind of computer readable storage medium, is stored thereon with computer program, execution when which is executed by processor
Following steps:
Step 1: while reading input of the multichannel live video stream as video flowing；
Step 2: the multichannel live video stream being spliced, splicing video flowing is obtained and is stored in splicing video fluxion
According to area；
Step 3: while the splicing video flowing of the data is read from splicing video stream data area, carry out moving object detection.
Each step involved in the device of above embodiments two and three is corresponding with embodiment of the method one, specific embodiment
It can be found in the related description part of embodiment one.Term " computer readable storage medium " is construed as including one or more
The single medium or multiple media of instruction set；It should also be understood as including any medium, any medium can be stored, be compiled
Code carries instruction set for being executed by processor and processor is made either to execute in the present invention method.
The present invention is handled splicing video flowing using multi-thread mechanism, so that video stream splicing and moving object detection
It carries out simultaneously parallel, without being pipeline system but parallel type, improves the operational efficiency of algorithm entirety.In video-splicing
The registration parameter between different video stream is calculated first to save into file, then for subsequent video stream, reads the registration ginseng
Number realizes fusion, realizes the real-time of video stream splicing.In moving object detection part, it is utilized in depth learning technology
Yolo algorithm completes moving object detection, relative to the target detection of traditional machine learning algorithm, speed and accuracy rate all
It is greatly improved.
It will be understood by those skilled in the art that each module or each step of aforementioned present invention can be filled with general computer
It sets to realize, optionally, they can be realized with the program code that computing device can perform, it is thus possible to which they are stored
Be performed by computing device in the storage device, perhaps they are fabricated to each integrated circuit modules or by they
In multiple modules or step be fabricated to single integrated circuit module to realize.The present invention is not limited to any specific hardware and
The combination of software.
Above-mentioned, although the foregoing specific embodiments of the present invention is described with reference to the accompanying drawings, not protects model to the present invention
The limitation enclosed, those skilled in the art should understand that, based on the technical solutions of the present invention, those skilled in the art are not
Need to make the creative labor the various modifications or changes that can be made still within protection scope of the present invention.
Claims (10)
1. a kind of trans-regional moving target detecting method based on video-splicing, which comprises the following steps:
Video-splicing process reads input of the multichannel live video stream as video flowing simultaneously；
The multichannel live video stream is spliced, splicing video flowing is obtained and is stored in splicing video stream data area；
Meanwhile detection process of moving target reads the splicing video flowing of the data from splicing video stream data area, carries out movement mesh
Mark detection.
2. the trans-regional moving target detecting method based on video-splicing as described in claim 1, which is characterized in that the side
After method carries out moving object detection further include: the moving target that will test is marked and shown in real time in video streaming.
3. the trans-regional moving target detecting method based on video-splicing as described in claim 1, which is characterized in that by multichannel
Live video stream carries out splicing
The multi-path video stream of reading is registrated, registration parameter is calculated and is saved；
For the multi-path video stream of subsequent reading, registration parameter is read, is merged based on the registration parameter.
4. the trans-regional moving target detecting method based on video-splicing as claimed in claim 3, which is characterized in that described right
The multi-path video stream of reading carries out registration
(1) feature extraction is carried out to the multi-path video stream of reading；
(2) feature of extraction is matched；
(3) according to the matching result of feature, camera parameter and homography matrix are calculated；
(4) image coordinate system of different video stream is mapped to by the same third-party spherical coordinate according to homography matrix；
(5) it is mapped in the same coordinate system according to different video stream homography conversion, calculates the overlapping between different video stream
Region；
(6) splicing seams between different video stream, calculated for subsequent are found in overlapping region dynamic using max-flow min-cut algorithm
Registration parameter simultaneously saves.
5. the trans-regional moving target detecting method based on video-splicing as claimed in claim 4, which is characterized in that subsequent
The multi-path video stream of reading merges
Registration parameter is read, homography conversion is carried out to the video flowing of subsequent reading；
The fusion of video flowing is carried out based on the registration parameter.
6. the trans-regional moving target detecting method based on video-splicing as described in claim 1, which is characterized in that the fortune
Moving-target detects
Target in monitoring video frame is labeled, as trained and test data set；
Based on trained and test data set training moving object detection model；
The splicing video flowing for reading splicing video stream data area in real time carries out moving object detection.
7. the trans-regional moving target detecting method based on video-splicing as claimed in claim 6, which is characterized in that the mark
Note includes the coordinate and classification information of label target.
8. the trans-regional moving target detecting method based on video-splicing as claimed in claim 6, which is characterized in that the fortune
Moving-target detection model is based on DarkNet frame application yolo network model.
9. a kind of trans-regional moving object detection device based on video-splicing, including memory, processor and it is stored in storage
On device and the computer program that can run on a processor, which is characterized in that the processor is realized such as when executing described program
Trans-regional moving target detecting method described in claim 1-8 based on video-splicing.
10. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is by processor
The trans-regional moving target detecting method according to claims 1-8 based on video-splicing is executed when execution.
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| CN109934848B (en) * | 2019-03-07 | 2023-05-23 | 贵州大学 | Method for accurately positioning moving object based on deep learning |
| CN109714623B (en) * | 2019-03-12 | 2021-11-16 | 北京旷视科技有限公司 | Image display method and device, electronic equipment and computer readable storage medium |
| CN113873200B (en) * | 2021-09-26 | 2024-02-02 | 珠海研果科技有限公司 | Image identification method and system |
| CN114222162B (en) * | 2021-12-07 | 2024-04-12 | 浙江大华技术股份有限公司 | Video processing method, device, computer equipment and storage medium |
| CN114842028A (en) * | 2022-05-07 | 2022-08-02 | 深圳先进技术研究院 | Cross-video target tracking method, system, electronic equipment and storage medium |
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