CN102917207A - Motion sequence based abnormal motion vision monitoring system - Google Patents
Motion sequence based abnormal motion vision monitoring system Download PDFInfo
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- CN102917207A CN102917207A CN2012104090205A CN201210409020A CN102917207A CN 102917207 A CN102917207 A CN 102917207A CN 2012104090205 A CN2012104090205 A CN 2012104090205A CN 201210409020 A CN201210409020 A CN 201210409020A CN 102917207 A CN102917207 A CN 102917207A
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Abstract
A motion sequence based abnormal motion vision monitoring system mainly includes the steps of extracting moving humans in vision field, detecting motion portions of the human body and judging whether abnormal motions exist or not. Specifically, the steps include: extracting a video, performing Gaussian background modeling by the video, extracting moving humans in the video, extracting outlines and matrix feature information of a target in a foreground, calling an intelligent comparison module, comparing the feature information of the foreground with abnormal motion feature base of humans, and judging whether abnormal motions of humans exist in the foreground; sending an alarm until the alarm is removed manually if the abnormal motions to be monitored exist; if not, keeping analyzing the next frame. The motion sequence based abnormal notion vision monitoring system is an intelligent video monitoring system centered in recognizing the abnormal motions of humans and capable of recognizing abnormal motions of humans, and can recognize abnormal motions from the videos and manage information of the abnormal motions.
Description
Technical field: patent of the present invention relates to image processing, computer vision, pattern recognition and electronic information field, a kind of passing through video content analysis, therefrom identify the swinging arm, kick the people, wrestle of people, embrace and the abnormal operation of fighting such as fall, prevent the generation of contingency, guarantee good public order.
Background technology: existing monitor and control facility, only have supervisory function bit only, can not identify people's abnormal behaviour, inadequate for the quick reaction capability of accident.Intelligent Video Surveillance Technology is to be derived from computer vision technique, is artificial intelligence study's a branch, and it sets up mapping relations between image and iamge description, thereby makes computer and analyze the content of understanding in the video pictures by Digital Image Processing.Intelligent monitoring technology is applied in the management of public place and some special occasions, can improves the efficient of management, prevent the generation of contingency.
Summary of the invention: for deficiency and the improvement that remedies existing supervisory control system has the defectives such as abnormal behaviour that intelligent monitor system can not be identified the people now, the present invention is centered by identification people's abnormal behaviour, set up an intelligent video monitoring system that can identify people's abnormal operation, wherein people's abnormal operation mainly comprises: swing arm, kick, wrestle, embrace and fall etc.This system is that the behavior act parser of combined with intelligent can realize the intelligentized unusual action behavior that identifies from video take network video monitor and control system as the basis, and the video frequency monitoring system that abnormal behaviour information is managed.
For achieving the above object, the technical solution used in the present invention is: the abnormal behaviour visual monitoring system of based on motion sequence, comprise the video information acquisition module (such as rig camera) that connects successively, video information sending module (such as fiber optic transmitter), video information transmission module (such as optical fiber or coaxial cable), video information receiver module (such as fiber optic receiver) and video information analysis and processing module (such as computer server and siren).According to the difference of application scenario, the remote distance video transfer signal demand adopts optical fiber, closely adopts coaxial cable can satisfy transmission requirement.The video information acquisition module with video information transmission to the video information sending module, the video information sending module is transferred to the video information receiver module by the video information transmission module after with video information coding, the video information receiver module with video information transmission to the video information analysis and processing module.
The key step of abnormal operation recognition methods of the present invention is to extract the motive position of the human body that moves in the visual field, human body, determine whether abnormal operation.At first extract one section video, utilize this section video to carry out the Gaussian Background modeling, extract the human body that moves in the video, then the profile of target and moment characteristics information are called intelligent comparing module in the extraction prospect, and the characteristic information of prospect and people's abnormal operation feature database are compared, judge the abnormal behaviour that whether has the people in this prospect, if the abnormal behaviour that will monitor is just sent warning, until artificial the releasing reported to the police; Otherwise continue to analyze next frame.
Being described in detail of several committed steps wherein is as follows:
1. set up people's abnormal operation feature database;
People's abnormal operation feature database is the priori of identification people's abnormal operation, so the behavioural characteristic storehouse of Erecting and improving is conducive to improve the accuracy of the abnormal operation of identifying the people.The method for building up of people's abnormal operation feature database mainly is to collect the photo that different people is done the different visual angles of same abnormal operation, and the feature database that corresponding feature consists of this action is extracted in these actions.
2. extraction video-frequency band, segmentation object;
What video analytics server received from fibre optic receiver in this invention is a bit of video, utilizes this section video to carry out the Gaussian Background modeling, obtains the human body that moves in this video channel, extracts the position of human body or the human body of motion with this from the background of complexity.
3. extraction target signature, the contrast characteristic storehouse is made identification and is judged;
Profile and the moment characteristics of the target that the extraction second step is partitioned into, and the abnormal operation feature in the feature database that this feature and the first step are set up compares, utilize Euclidean distance between feature to judge the similarity of the two, when similarity is enough high, just think that this target is abnormal operation, otherwise do not think that the target of extracting is abnormal operation.
4. send warning, recording exceptional information;
If the 3rd walks out of existing warning, then this section video is saved in assigned address take the date as filename, and ejects corresponding alarm signal at monitoring interface, or send corresponding audible ringing signal.
The present invention sets up an intelligent video monitoring system that can identify people's abnormal operation centered by identification people's abnormal behaviour, this system can identify unusual action behavior from video, and abnormal behaviour information is managed.
Description of drawings:
Fig. 1 is hardware composition frame chart of the present invention.
Fig. 2 is operation principle block diagram of the present invention.
Embodiment:
As shown in Figure 1: hardware composition of the present invention mainly contains: video information acquisition module (such as rig camera), video information sending module (such as fiber optic transmitter), video information transmission module (such as optical fiber or coaxial cable), video information receiver module (such as fiber optic receiver), video information analysis and processing module (such as computer server and siren).According to the difference of application scenario, the remote distance video transfer signal demand adopts optical fiber, closely adopts coaxial cable can satisfy transmission requirement.
The image transmitting that video camera is taken is to fiber optic transmitter, fiber optic transmitter with video information coding after by Optical Fiber Transmission to the fibre optic receiver in the control room, the intelligent video analysis server obtains the video information of each passage video camera from fibre optic receiver by timeslice mode in turn, video information is presented on the monitoring interface of server, meanwhile this section video information is carried out intellectual analysis, if note abnormalities action behavior, then send alarm signal at monitoring interface.This system can utilize commercially available rig camera, fiber optical transceiver and server to form.
The recognition methods of above-mentioned intelligent vision abnormal operation is written as the form of application software, and moves at server.Whether the video information of at first checking each passage can correctly gather, and sets up the abnormal behaviour database; Then operation exception action recognition application program is monitored each passage.
As shown in Figure 2: extract first one section video, utilize this section video to carry out the Gaussian Background modeling, extract the human body that moves in the video, then the profile of target and moment characteristics information are called intelligent comparing module in the extraction prospect, and characteristic information and the property data base of prospect compared, judge the abnormal behaviour that whether has the people in this prospect, if the abnormal behaviour that will monitor is just sent warning, until artificial the releasing reported to the police; Otherwise continue to analyze next frame.
Claims (8)
1. the abnormal behaviour visual monitoring system of based on motion sequence is characterized in that: comprise the video information acquisition module that connects successively, video information sending module, video information transmission module, video information receiver module and video information analysis and processing module; The video information acquisition module with image transmitting to the video information module, the video information module is transferred to the video information receiver module by the video information transmission module after with video information coding, the video information receiver module with communication to the video information analysis and processing module.
2. the abnormal behaviour visual monitoring system of based on motion sequence as claimed in claim 1, it is characterized in that: described video information acquisition module is rig camera.
3. the abnormal behaviour visual monitoring system of based on motion sequence as claimed in claim 1, it is characterized in that: described video information sending module is fiber optic transmitter.
4. the abnormal behaviour visual monitoring system of based on motion sequence as claimed in claim 1, it is characterized in that: described video information transmission module is optical fiber or coaxial cable.
5. the abnormal behaviour visual monitoring system of based on motion sequence as claimed in claim 1, it is characterized in that: described video information receiver module is fiber optic receiver.
6. the abnormal behaviour visual monitoring system of based on motion sequence as claimed in claim 1, it is characterized in that: described video information analysis and processing module is computer server and siren.
7. the abnormal behaviour visual monitoring recognition methods of based on motion sequence, adopt monitoring system as claimed in claim 1, concrete steps are: at first extract one section video, utilize this section video to carry out the Gaussian Background modeling, extract the moving target in the video, then the profile of target and moment characteristics information in the extraction prospect, call intelligent comparing module, the characteristic information of prospect and people's abnormal operation feature database are compared, judge the abnormal behaviour that whether has the people in this prospect, if the abnormal behaviour that will monitor is just sent warning, until artificial the releasing reported to the police; Otherwise continue to analyze next frame.
8. the abnormal behaviour visual monitoring recognition methods of based on motion sequence as claimed in claim 7, it is characterized in that: the method for building up of described people's abnormal operation feature database mainly is to collect the photo that different people is done the different visual angles of same abnormal operation, and the feature database that corresponding feature consists of this action is extracted in these actions.
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| CN2012104090205A CN102917207A (en) | 2012-10-24 | 2012-10-24 | Motion sequence based abnormal motion vision monitoring system |
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Cited By (13)
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| CN104029008A (en) * | 2013-03-07 | 2014-09-10 | 康耐视公司 | System And Method For Aligning Two Work Pieces With Vision System In The Presence Of Occlusion |
| CN104077591A (en) * | 2013-03-27 | 2014-10-01 | 冉祥 | Intelligent and automatic computer monitoring system |
| CN104301686A (en) * | 2014-10-27 | 2015-01-21 | 青岛宝微视控信息技术有限公司 | Intelligent video analyzing system and method |
| CN104299355A (en) * | 2014-09-28 | 2015-01-21 | 厦门蓝斯通信股份有限公司 | Vehicle monitoring method and system based on video intelligent recognition |
| CN106571014A (en) * | 2016-10-24 | 2017-04-19 | 上海伟赛智能科技有限公司 | Method for identifying abnormal motion in video and system thereof |
| CN106851229A (en) * | 2017-04-01 | 2017-06-13 | 山东瀚岳智能科技股份有限公司 | A kind of method and system of the security protection intelligent decision based on image recognition |
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| CN110472458A (en) * | 2018-05-11 | 2019-11-19 | 深眸科技(深圳)有限公司 | A kind of unmanned shop order management method and system |
| CN110826492A (en) * | 2019-11-07 | 2020-02-21 | 长沙品先信息技术有限公司 | Method for detecting abnormal behaviors of crowd in sensitive area based on behavior analysis |
| CN111767783A (en) * | 2020-04-22 | 2020-10-13 | 杭州海康威视数字技术股份有限公司 | Behavior detection method, behavior detection device, model training method, model training device, electronic equipment and storage medium |
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| CN106856063A (en) * | 2015-12-09 | 2017-06-16 | 朱森 | A kind of new teaching platform |
| CN106571014A (en) * | 2016-10-24 | 2017-04-19 | 上海伟赛智能科技有限公司 | Method for identifying abnormal motion in video and system thereof |
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| CN106851229A (en) * | 2017-04-01 | 2017-06-13 | 山东瀚岳智能科技股份有限公司 | A kind of method and system of the security protection intelligent decision based on image recognition |
| CN109658660A (en) * | 2017-10-12 | 2019-04-19 | 中兴通讯股份有限公司 | Alarm method, warning device and storage medium |
| CN109658660B (en) * | 2017-10-12 | 2021-09-14 | 中兴通讯股份有限公司 | Alarm method, alarm device and storage medium |
| CN110472458A (en) * | 2018-05-11 | 2019-11-19 | 深眸科技(深圳)有限公司 | A kind of unmanned shop order management method and system |
| CN110826492A (en) * | 2019-11-07 | 2020-02-21 | 长沙品先信息技术有限公司 | Method for detecting abnormal behaviors of crowd in sensitive area based on behavior analysis |
| CN111767783A (en) * | 2020-04-22 | 2020-10-13 | 杭州海康威视数字技术股份有限公司 | Behavior detection method, behavior detection device, model training method, model training device, electronic equipment and storage medium |
| CN111986416A (en) * | 2020-08-31 | 2020-11-24 | 安徽中烟工业有限责任公司 | Safety protection system and method for operation inside roller |
| CN111986416B (en) * | 2020-08-31 | 2022-05-31 | 安徽中烟工业有限责任公司 | Safety protection system and method for operation inside roller |
| CN112489359A (en) * | 2020-12-09 | 2021-03-12 | 江西珉轩大数据有限公司 | Abnormal event early warning system for smart community |
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Application publication date: 20130206 |