CN102799935A - Human flow counting method based on video analysis technology - Google Patents
Human flow counting method based on video analysis technology Download PDFInfo
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Abstract
The invention discloses a human flow counting method based on a video analysis technology, and relates to an intelligent video analysis technology. The counting method comprises the following steps of: (1) training a human head feature model; (2) acquiring a foreground point of a moving object by using an inter-frame difference; (3) performing human head feature extraction and identification; (4) performing human body local feature identification; (5) performing human head feature region tracking; and (6) performing human flow counting. The performance is stable, speed and efficiency are high, and the false alarm rate is low; and generality, portability and extensibility are high, and the method is suitable for equipment of various manufacturers and various intelligent video analysis systems.
Description
Technical field
The present invention relates to the video intelligent analytical technology, relate in particular to the people flow rate statistical method based on the video analysis technology of looking a kind of.
Background technology
In video intelligent analysis system; People flow rate statistical is a critical function of this system; It can effectively be applied to the people flow rate statistical of public places such as market, bus, gateway, airport, subway station gateway, exhibition venue gateway; Through zones of different is gathered, excavates, contrasts and analyze with different period flow of the people data, for user management and decision-making provide important evidence.
Present existing people flow rate statistical method mainly is:
1, " based on the people flow rate statistical method and system of intelligent video identification technology ", applicant: Xinlian-Weixun Science & Technology Development Co Ltd, Shanghai // Chinese patent, application number: 200810037799.Obtain the body templates in the current frame video image according to the information scanning in the standard body templates database, then two preceding line directions of body templates are judged, and then the flow of the people on the statistics both direction.
2, " based on the pedestrian's flow statistical method and the system of traffic monitoring facility ", applicant: Beijing Jiaotong University // Chinese patent, application number: 201010155338.In detection block, carry out the number of people according to normal man's head mould plate and detect, judge whether the detected number of people presses detection line, thereby confirm the effective number of people number in the detection block.Mate with previous testing result then, and the number of people of different motion direction is counted according to matching result.According to the situation that is provided with of detection block and detection line, carry out traffic statistics at last.
Method 1 scanning obtains the body templates in the current frame video image, and body templates is applied in and often has more blocking in the actual scene; Method 2 mainly is to detect the number of people, between the number of people to block probability littler, but detecting false-alarm also can correspondingly increase.
Summary of the invention
The objective of the invention is to overcome the shortcoming and defect that prior art exists, a kind of people flow rate statistical method based on the video analysis technology is provided.
The objective of the invention is to realize like this:
Adopt frame-to-frame differences method and a kind of body local characteristic (number of people and shoulder combine) to detect recognition technology based on statistic pattern recognition theory.Adopt frame-to-frame differences to obtain the foreground point information of moving object, number of people feature detection is carried out in the foreground point of motion, improve the speed and minimizing wrong report of algorithm.Adopt body local characteristic (number of people and shoulder combine) to detect strategy, can eliminate detected false-alarm effectively, improve the accuracy rate of algorithm, be applicable to the scene that the various stream of peoples are more.
One, a kind of people flow rate statistical system (abbreviation statistical system) based on the video analysis technology
This statistical system comprises working environment: video monitoring platform, comprehensive access gate, intelligent management server;
Be provided with the intellectual analysis server;
Its annexation is: video monitoring platform, comprehensive access gate, intelligent management server and intellectual analysis server are connected successively.
Principle of work
The intellectual analysis server is connected to intelligent management server, and the intellectual analysis server is connected to intelligent management server according to the IP (Internet protocol) and the port of intelligent management server; When the user asked the video intelligent analysis task, this request sent to intelligent management server, and intelligent management server 30 is noted the intellectual analysis server state; And with the balanced intellectual analysis server that is assigned to the free time of camera tabulation to be detected, intellectual analysis server taking turn equipment obtains real-time video and decoding from camera; Obtain RGB (red, green, blue; RGB) data; Then the RGB data are analyzed, and testing result is reported to intelligent management server, intelligent management server is preserved the result get off.The user also can report to the police according to alarm type and date inquiry, and statistics generates form.
Two, a kind of people flow rate statistical method (abbreviation statistical method) based on the video analysis technology
Like Fig. 2, this statistical method comprises step:
1. train number of people characteristic model-201
To gradient orientation histogram characteristic (hog) the sample training of the number of people, generate number of people characteristic model, promptly generate number of people gradient orientation histogram feature samples model;
2. frame-to-frame differences obtains the foreground point-202 of moving object
Adopt the frame-to-frame differences method to obtain the foreground point information of moving object;
3. number of people feature extraction and identification-203
To the feature extraction algorithm of the image applications behind the frame-to-frame differences based on statistics, the target in the detected image is mated detected target and sample pattern, tentatively confirms the number of people characteristic area in this two field picture;
4. body local feature identification-204
Whether it exists the shoulder characteristic to detected number of people region decision, when there being the shoulder characteristic, then is number of people characteristic area, otherwise is non-number of people characteristic area;
5. number of people characteristic area follows the tracks of-205
Employing is followed the tracks of the detected number of people based on the tracking technique that matees and target following combines, and obtains pedestrian's movement locus, and the frame number that number of people characteristic area occurs is added up;
6. the flow of the people counting-206
Does when number of people target is crossed line with the zone by assigned direction, and the frame number that number of people target occurs satisfy certain condition (what condition?) time, the pedestrian is carried out the counting on the assigned direction, add up the flow of the people on this direction.
The present invention has advantage and good effect:
1, stable performance, speed is fast, and efficient height and rate of false alarm are low;
2, highly versatile is applicable to the equipment of each producer;
3, portable strong, extendability is flexible;
4, be applicable to all kinds of video intelligent analysis system.
Description of drawings
Fig. 1 is this statistical system block diagram, among the figure
The 10-video monitoring platform,
11-the 1 video monitoring platform,
12-the 2nd video monitoring platform
1N-N video monitoring platform, N is a natural number, N < 10;
The 20-comprehensive access gate;
The 30-intelligent management server;
40-intellectual analysis server,
41-the 1st intellectual analysis server
4N-N intellectual analysis server, N is a natural number, N < 100.
Fig. 2 is this statistical method block diagram.
Fig. 3 sets up number of people sample pattern method flow diagram.
Fig. 4 is a number of people object detection method process flow diagram.
Fig. 5 is people head's tracking detection method process flow diagram.
Embodiment
Specify below in conjunction with accompanying drawing and embodiment:
One, statistical system
1, overall
Like Fig. 1, this statistical system comprises working environment: video monitoring platform 10, comprehensive access gate 20, intelligent management server 30;
Be provided with intellectual analysis server 40;
Its annexation is: video monitoring platform 10, comprehensive access gate 20, intelligent management server 30 and intellectual analysis server 40 are connected successively.
2, functional part
1) video monitoring platform 10
The business such as remote collection, transmission, storage and processing of real-time audio and video and various alerting signals are provided for the user.
2) comprehensive access gate 20
The statistics that realizes video monitoring platform inserts.
3) intelligent management server 30
Realize intelligence resource management, be in charge of the intellectual analysis resource.
4) the intellectual analysis server 40
Intellectual analysis server 40 is functional entitys that video intelligent is analyzed, a corresponding station server on physical distribution.Intellectual analysis server 40 is made up of a plurality of VA (video analysis unit), and each VA can independently accomplish the intellectual analysis of one road video.
Major function is:
1. realize the video intelligent analytical algorithm;
2. be linked into intelligent management server 30, by intelligent management server 30 centralized management;
3. receive the video intelligent analysis request of intelligent management server 30, obtain video and analyze from video monitoring platform 10;
4. diagnostic result is reported intelligent management server 30.
A kind of people flow rate statistical method based on the video analysis technology of the present invention is implemented in the VA module of intellectual analysis server 40.
Specifically, the VA module of intellectual analysis server 40 comprises general-purpose computer and implants the functional software in the computer.
Two, statistical method
Like Fig. 2, this statistical method is a kind of people flow rate statistical method based on the video analysis technology in the summary of the invention.
1, sets up number of people sample pattern method
This method mainly is to adopt svm (supporting/hold vector machine) sorter to set up number of people feature samples model, and for people head's sign supplies model indescribably, the step that relates to total method 1..
Like Fig. 3, performing step is following:
1. import number of people feature samples-301, import non-number of people feature samples-302;
2. the sample to input carries out hog feature extraction-303, obtains the proper vector of sample;
3. use svm sorter-304, the proper vector of input is trained;
4. through the computing of svm, obtain the model-305 of number of people characteristic.
2, the detection method of number of people characteristic
This method mainly is to adopt the frame-to-frame differences method to obtain the foreground information of moving object to video image; Extract foreground point hog characteristic; And detected target and number of people feature samples masterplate mated; Judge to mating successful number of people characteristic area whether it exists the shoulder characteristic, thereby distinguish number of people characteristic area and non-number of people characteristic area effectively that the step that relates to total method 2. 3. 4..
Like Fig. 4, performing step is following:
Hog is histogram of oriented gradient; It is feature description that is used for target detection; This technology is counted the direction gradient number of times that image local occurs; This method and edge orientation histogram, scale-invariant feature transform are similar, and the calculating of different is hog improves accuracy rate based on the density matrix of uniform space.
1. frame-to-frame differences obtains the foreground point information-401 of moving object;
2. extract foreground point hog characteristic-402, obtain its proper vector;
3. with the hog feature extraction to proper vector and number of people characteristic model-403 mate-404, ask for candidate's number of people characteristic area-405 and non-number of people characteristic area-406;
4. judge to mating successful candidate's number of people characteristic area whether it exists shoulder characteristic-407, when there being the shoulder characteristic, then be number of people characteristic area-408, otherwise be non-number of people characteristic area-409.
3, number of people characteristic area tracking
This method mainly is to adopt the number of people characteristic area tracking technique that combines based on coupling and CamShift (self-adaptation mean shift track algorithm continuously), is used for the tracking and the location of number of people characteristic area, and the step that relates to total method 5..
Like Fig. 5, performing step is following:
1. detected number of people characteristic area-502 of previous frame and the detected number of people characteristic area-501 of present frame are carried out centre distance coupling-503;
2. when mating successfully, then the detected target of present frame is a number of people characteristic area-504, and record present frame number of people target area is complete, otherwise gets into step 3.;
3. adopt the camshift track algorithm to follow the tracks of-505 to previous frame number of people target area, obtain the number of people characteristic area tracing positional of present frame;
4. the present frame number of people characteristic area of camshift being obtained is as tracking results-506, and notes.
Claims (4)
1. the people flow rate statistical method based on the video analysis technology is characterized in that comprising the following steps:
1. train number of people characteristic model (201)
Gradient orientation histogram feature samples to the number of people is trained, and generates number of people characteristic model, promptly generates number of people gradient orientation histogram feature samples model;
2. frame-to-frame differences obtains the foreground point (202) of moving object
Adopt the frame-to-frame differences method to obtain the foreground point information of moving object;
3. number of people feature extraction and identification (203)
To the feature extraction algorithm of the image applications behind the frame-to-frame differences based on statistics, the target in the detected image is mated detected target and sample pattern, tentatively confirms the number of people characteristic area in this two field picture;
4. body local feature identification (204)
Whether it exists the shoulder characteristic to detected number of people region decision, when there being the shoulder characteristic, then is number of people characteristic area, otherwise is non-number of people characteristic area;
5. number of people characteristic area is followed the tracks of (205)
Employing is followed the tracks of the detected number of people based on the tracking technique that matees and target following combines, and obtains pedestrian's movement locus, and the frame number that number of people characteristic area occurs is added up;
6. flow of the people is counted (206)
When number of people target is crossed line and when zone by assigned direction, and the frame number that occurs of number of people target carries out the counting on the assigned direction to the pedestrian when being N, adds up the flow of the people on this direction, and wherein N is a natural number, and 1 < N < 200.
2. by the described a kind of people flow rate statistical method based on the video analysis technology of claim 1, it is following to it is characterized in that setting up number of people sample pattern method performing step:
1. import number of people feature samples (301), import non-number of people feature samples (302);
2. the sample to input carries out hog feature extraction (303), obtains the proper vector of sample;
3. use svm sorter (304), the proper vector of input is trained;
4. through the computing of svm, obtain the model (305) of number of people characteristic.
3. by the described a kind of people flow rate statistical method of claim 1, it is characterized in that the detection method performing step of number of people characteristic is following based on the video analysis technology:
1. frame-to-frame differences obtains the foreground point information (401) of moving object;
2. extract foreground point hog characteristic (402), obtain its proper vector;
3. with the hog feature extraction to proper vector and number of people characteristic model (403) mate (404), ask for candidate's number of people characteristic area (405) and non-number of people characteristic area (406);
4. judge to mating successful candidate's number of people characteristic area whether it exists shoulder characteristic (407), when there being the shoulder characteristic, then be number of people characteristic area (408), otherwise be non-number of people characteristic area (409).
4. by the described a kind of people flow rate statistical method of claim 1, it is characterized in that the performing step of number of people characteristic area tracking is following based on the video analysis technology:
1. detected number of people characteristic area of previous frame (502) and the detected number of people characteristic area of present frame (501) are carried out centre distance coupling (503);
2. when mating successfully, then the detected target of present frame is number of people characteristic area (504), and record present frame number of people target area is complete, otherwise gets into step 3.;
3. adopt the camshift track algorithm to follow the tracks of (505) to previous frame number of people target area, obtain the number of people characteristic area tracing positional of present frame;
4. the present frame number of people characteristic area of camshift being obtained is as tracking results (506), and notes.
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| CN103021059A (en) * | 2012-12-12 | 2013-04-03 | 天津大学 | Video-monitoring-based public transport passenger flow counting method |
| CN103390172A (en) * | 2013-07-24 | 2013-11-13 | 佳都新太科技股份有限公司 | Estimating method of crowd density under high-density scene |
| CN103473554A (en) * | 2013-08-19 | 2013-12-25 | 上海汇纳网络信息科技有限公司 | People flow statistical system and people flow statistical method |
| CN103824114A (en) * | 2014-01-26 | 2014-05-28 | 中山大学 | Pedestrian flow counting method and system based on section flow statistics |
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