CN101917604A - Intelligent analysis method for video images in rail transit - Google Patents
Intelligent analysis method for video images in rail transit Download PDFInfo
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- CN101917604A CN101917604A CN 201010271880 CN201010271880A CN101917604A CN 101917604 A CN101917604 A CN 101917604A CN 201010271880 CN201010271880 CN 201010271880 CN 201010271880 A CN201010271880 A CN 201010271880A CN 101917604 A CN101917604 A CN 101917604A
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Abstract
The invention relates to a monitoring device, in particular to an intelligent analysis method for video monitoring images in rail transit. In the method, a camera is used for collecting the image information of a monitoring area in the rail transit, and the image information is transmitted to a monitor so as to monitor the rail transit. The method is characterized by comprising the following steps of: transmitting the image information in a digital mode to a video analysis server through a switch after the camera collects the image information; comparing and analyzing the image signal and a preset alert threshold by a video analysis module in the video analysis server; transmitting the image information triggering the alert threshold as selected image information to a video control server through the switch; and finally, controlling the selected image signal by the video control server to output the selected image signal to the monitor to be displayed. The invention has the advantages of reducing the working strength of manual monitoring and improving working efficiency and monitoring effect.
Description
Technical field
The present invention relates to the supervising device class, be specifically related to a kind of video monitoring image intelligent analysis method that is used for track traffic.
Background technology
Along with track traffic constantly popularizing in the city, video monitoring system scale in subway, station and the interval, station is huge day by day, number of cameras constantly increases, the video monitoring content is also more and more in the track traffic, if adopt traditional video monitoring means, then need to increase a large amount of monitors and call great amount of manpower and could effectively monitor track traffic.
So, in track traffic, adopt the intelligent image analytical technology imperative, there has been the intelligent image analytical technology in subway, to be applied abroad.But intelligent image is analyzed at home and is not formally carried out application as yet in the railway traffic engineering, its set place, quantity, analytical model all differ from routine because of being subjected to on-the-spot too intensive passenger flow factor affecting, the external pattern of using can't be applied directly to domestic subway industry, obtain an investment rationally and the obvious results system schema need carry out big quantitative statistics, analysis and comparative studies.
Summary of the invention
The objective of the invention is according to above-mentioned the deficiencies in the prior art part, a kind of video monitoring image intelligent analysis method that is used for track traffic is provided, this method realizes automatic monitoring, identification and the alarm linkage of abnormal conditions by switch, monitor, video Control Server and the video analytics server of star topology coupling are set.
The object of the invention realizes being finished by following technical scheme:
A kind of video monitoring image intelligent analysis method that is used for track traffic, this method adopts the image information of guarded region in the camera acquisition track traffic, and image information transferred on the monitor to realize the monitoring for track traffic, it is characterized in that: after the described camera acquisition image information, described image information is transferred in the video analytics server by switch with figure pattern, analysis module in the video analytics server is analyzed described picture signal and preset alarm threshold value, the image information that will trigger alarm threshold afterwards transfers in the video Control Server by described switch as selected image information, controls selected picture signal by described video Control Server at last and exports in the described monitor and show.
Described comparative analysis step comprises the intrusion detection determining step: at first preset Off Limits in the image frame of corresponding guarded region respectively, when analysis module detects when having target to enter Off Limits in the image information of being gathered, trigger alarm threshold and report to the police.
Described comparative analysis step comprises staying and detects and suspicious object is left over the detection step: default respectively prohibition parking area territory in the image frame of corresponding guarded region at first, when analysis module detects the target of staying and surpasses the time of setting in prohibition parking area territory described in the image information of being gathered, trigger alarm threshold and report to the police.
Described comparative analysis step comprises the detection step of driving in the wrong direction: at first preset forbidden direction in the image frame of corresponding guarded region respectively, when analysis module detects in the image information of being gathered target with forbidden direction motion, trigger alarm threshold and report to the police.
Described comparative analysis step comprises that the passenger chases and strenuous exercise's monitoring step: at first preset guarded region in the image frame of corresponding guarded region respectively, when analysis module detects that the personnel targets in the guarded region has aggravating activities in the image information of being gathered, trigger alarm threshold and report to the police.
Described comparative analysis step comprises volume of the flow of passengers sudden change alarm step: at first preset guarded region in the image frame of corresponding guarded region respectively, when analysis module detects in the image information of being gathered personnel distribute in the guarded region unit are dense degree and increases suddenly in the unit interval, trigger alarm threshold and report to the police.
Described comparative analysis step comprises image abnormity alarm identification step: be shifted when analysis module detects camera lens, during situation such as vision signal input change or dropout, trigger alarm threshold and warning.
Described method also comprises the image storing step: described camera acquisition image information and with its digitlization, described video Control Server are controlled described image information and are transferred in the storage medium by described switch and store.
Described image storing step also comprises stream of people's statistic procedure: at first preset guarded region in the image frame of corresponding guarded region respectively, the analysis module statistics enters or leaves this regional number, and statistics is stored in the described storage medium.
Described video camera is analog video camera and/or digital camera, and described analog video camera is coupled by an encoder and a described switch that is used for digital-to-analogue conversion.
Advantage of the present invention is: realized automatic monitoring, identification and the alarm linkage of abnormal conditions in track traffic, reduced personal monitoring's working strength, increased work efficiency and monitoring effect.
Description of drawings
Accompanying drawing 1 is an apparatus structure schematic diagram of the present invention;
Accompanying drawing 2 is a schematic flow sheet of the present invention.
Embodiment
Feature of the present invention and other correlated characteristic are described in further detail by embodiment below in conjunction with accompanying drawing, so that technical staff's of the same trade understanding:
As shown in Figure 1, mark 1-10 is respectively among the figure: analog video camera 1, digital camera 2, encoder 3, switch 4, video Control Server 5, video analytics server 6, monitor 7, decoder 8, storage medium 9, client 10.
Referring to Fig. 1, the supervisory control system that the present invention relied on adopts the digital network networking mode, by switch 4 each composition is coupled and sets up a star topology network, to constitute the local monitor network system.
Wherein, video camera includes analog video camera 1 and digital camera 2, wherein the image gathered of analog video camera 1 changes digital signal into through video encoder 3, inserts the local monitor networks by switch 4, and 2 of digital cameras are directly in the access local monitor network.Switch 4 also is coupled with: decoder 8 is used for data image signal and is reduced into analog picture signal; Monitor 7 is used for the demonstration of camera acquisition image; Storage medium 9 is used for the storage of view data; Video Control Server 5, be configured to control view data in the demonstration of monitor 7 and the storage medium 9 storage, call; Video analytics server 6 is provided with and is used for analysis module, be used for the view data of described camera acquisition is analyzed selection, and the view data that will select shows on monitor 7 by video Control Server 5.
Analysis module in the video analytics server 6, be used for the associated camera image is carried out intellectual analysis, comprise: intrusion detection, stay that (delay) detects, suspicious object is left over detections, drive in the wrong direction detect, the passenger chases and strenuous exercise's monitoring, volume of the flow of passengers sudden change alarm, stream of people's statistics, application such as image abnormity alarm identification, alarm and displayed scene reorganization, can be shifted to camera lens simultaneously, vision signal imports situations such as change, dropout and detect and report to the police.In above-mentioned analytical procedure, when having detected violations of rules and regulations and take place, video analytics server 6 will notify video Control Server 5 that dependent picture is released automatically, in time dispose for operating personnel.
Analysis module specifically to analyse arbitration functions as follows:
Intrusion detection step: in picture, delimit Off Limits in advance, when system has detected target and enters Off Limits, trigger alarm threshold and report to the police;
Staying (delay) detects and suspicious object is left over the detection step: delimit the prohibition parking area territory in advance in picture, when system detects the target of staying and surpasses the time that the user sets in the prohibition parking area territory, trigger alarm threshold and report to the police;
Drive in the wrong direction to detect step: in picture, preestablish forbidden direction, when system detects target by forbidden direction motion, trigger alarm threshold and report to the police;
The passenger chases and strenuous exercise's monitoring step: delimit guarded region in advance in picture, when the personnel targets in system detects guarded region has aggravating activities, trigger alarm threshold and warning;
Volume of the flow of passengers sudden change alarm step: delimit guarded region in picture in advance, when the dense degree that personnel distribute in system detects the guarded region unit are increased suddenly in the unit interval, the triggering alarm threshold was also reported to the police;
Image abnormity alarm identification step: be shifted when system detects camera lens, during situation such as vision signal input change or dropout, trigger alarm threshold and warning;
Alarm and displayed scene reorganization: refer to that system can independently provide before the alarm and the alarm video recording of (period) constantly according to Real-time Alarm and the recovering information that different detected object provided;
Stream of people statistics: delimit guarded region in picture in advance, system will add up automatically and enter or leave this regional number, and the view data that will gather with this moment statistical number of person be stored in the storage medium 9.
Claims (10)
1. video image intelligent analysis method that is used for track traffic, this method adopts the image information of guarded region in the camera acquisition track traffic, and image information transferred on the monitor to realize the monitoring for track traffic, it is characterized in that: after the described camera acquisition image information, described image information is transferred in the video analytics server by switch with figure pattern, analysis module in the video analytics server is analyzed described picture signal and preset alarm threshold value, the image information that will trigger alarm threshold afterwards transfers in the video Control Server by described switch as selected image information, controls selected picture signal by described video Control Server at last and exports in the described monitor and show.
2. a kind of video image intelligent analysis method that is used for track traffic according to claim 1, it is characterized in that described comparative analysis step comprises the intrusion detection determining step: at first in the image frame of corresponding guarded region, preset Off Limits respectively, when analysis module detects when having target to enter Off Limits in the image information of being gathered, trigger alarm threshold and report to the police.
3. a kind of video image intelligent analysis method that is used for track traffic according to claim 1, it is characterized in that described comparative analysis step comprises staying detects and suspicious object is left over the detection step: default respectively prohibition parking area territory in the image frame of corresponding guarded region at first, when analysis module detects the target of staying and surpasses the time of setting in prohibition parking area territory described in the image information of being gathered, trigger alarm threshold and report to the police.
4. a kind of video image intelligent analysis method that is used for track traffic according to claim 1, it is characterized in that described comparative analysis step comprises the detection step of driving in the wrong direction: at first in the image frame of corresponding guarded region, preset forbidden direction respectively, when analysis module detects in the image information of being gathered target with forbidden direction motion, trigger alarm threshold and report to the police.
5. a kind of video image intelligent analysis method that is used for track traffic according to claim 1, it is characterized in that described comparative analysis step comprises that the passenger chases and strenuous exercise's monitoring step: at first in the image frame of corresponding guarded region, preset guarded region respectively, when analysis module detects that the personnel targets in the guarded region has aggravating activities in the image information of being gathered, trigger alarm threshold and report to the police.
6. a kind of video image intelligent analysis method that is used for track traffic according to claim 1, it is characterized in that described comparative analysis step comprises volume of the flow of passengers sudden change alarm step: at first in the image frame of corresponding guarded region, preset guarded region respectively, when analysis module detects in the image information of being gathered personnel distribute in the guarded region unit are dense degree and increases suddenly in the unit interval, trigger alarm threshold and report to the police.
7. a kind of video image intelligent analysis method that is used for track traffic according to claim 1, it is characterized in that described comparative analysis step comprises image abnormity alarm identification step: be shifted when analysis module detects camera lens, during situation such as vision signal input change or dropout, trigger alarm threshold and warning.
8. a kind of video image intelligent analysis method that is used for track traffic according to claim 1, it is characterized in that described method also comprises the image storing step: described camera acquisition image information and with its digitlization, described video Control Server are controlled described image information and are transferred in the storage medium by described switch and store.
9. a kind of video image intelligent analysis method that is used for track traffic according to claim 8, it is characterized in that described image storing step also comprises stream of people's statistic procedure: at first in the image frame of corresponding guarded region, preset guarded region respectively, the analysis module statistics enters or leaves this regional number, and statistics is stored in the described storage medium.
10. a kind of video image intelligent analysis method that is used for track traffic according to claim 1, it is characterized in that: described video camera is analog video camera and/or digital camera, and described analog video camera is coupled by an encoder and a described switch that is used for digital-to-analogue conversion.
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Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102279779A (en) * | 2011-08-29 | 2011-12-14 | 杭州海康威视数字技术股份有限公司 | Method and device for realizing redundancy backup of video data on digital video recorder |
| CN103475872A (en) * | 2013-10-02 | 2013-12-25 | 哈尔滨理工大学 | Railway abnormal object detecting device based on cloud vision |
| CN104284161A (en) * | 2014-10-30 | 2015-01-14 | 中国二十二冶集团有限公司 | Star-shaped divergent digital video monitoring system |
| CN104820995A (en) * | 2015-04-21 | 2015-08-05 | 重庆大学 | Large public place-oriented people stream density monitoring and early warning method |
| CN105160793A (en) * | 2015-09-01 | 2015-12-16 | 小米科技有限责任公司 | Alarming method and apparatus |
| CN105182839A (en) * | 2015-07-20 | 2015-12-23 | 柳州一健科技有限公司 | Method for controlling driving unit of self-propelled engineering machinery |
| CN105611251A (en) * | 2015-12-30 | 2016-05-25 | 成都移动魔方科技有限公司 | Real time security monitoring method |
| CN106205143A (en) * | 2016-08-29 | 2016-12-07 | 苏州金螳螂怡和科技有限公司 | Intelligent bayonet networked system |
| CN106331629A (en) * | 2016-08-29 | 2017-01-11 | 合肥康胜达智能科技有限公司 | Safety monitoring system |
| CN106530711A (en) * | 2016-12-16 | 2017-03-22 | 合肥寰景信息技术有限公司 | Video image intelligent traffic analysis method for high-speed vehicle |
| CN107318039A (en) * | 2017-08-15 | 2017-11-03 | 龙岩龙安安全科技有限公司 | A kind of intelligent pop-up monitoring and warning system |
| CN107426009A (en) * | 2017-05-24 | 2017-12-01 | 上海三吉电子工程有限公司 | Subway communication network management system |
| CN109495718A (en) * | 2018-11-02 | 2019-03-19 | 深圳市北斗智能科技有限公司 | Monitor video acquisition methods, device and computer readable storage medium |
| CN109753893A (en) * | 2018-12-20 | 2019-05-14 | 广州航天海特系统工程有限公司 | Video detecting method, system, computer equipment and storage medium along track |
| CN113256924A (en) * | 2020-02-12 | 2021-08-13 | 中车唐山机车车辆有限公司 | Monitoring system, monitoring method and monitoring device for rail train |
| CN114463949A (en) * | 2022-02-07 | 2022-05-10 | 中铁大桥勘测设计院集团有限公司武汉分公司 | Station platform boundary-crossing alarm device of passenger station house |
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Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102279779A (en) * | 2011-08-29 | 2011-12-14 | 杭州海康威视数字技术股份有限公司 | Method and device for realizing redundancy backup of video data on digital video recorder |
| CN103475872A (en) * | 2013-10-02 | 2013-12-25 | 哈尔滨理工大学 | Railway abnormal object detecting device based on cloud vision |
| CN104284161A (en) * | 2014-10-30 | 2015-01-14 | 中国二十二冶集团有限公司 | Star-shaped divergent digital video monitoring system |
| CN104820995A (en) * | 2015-04-21 | 2015-08-05 | 重庆大学 | Large public place-oriented people stream density monitoring and early warning method |
| CN105182839A (en) * | 2015-07-20 | 2015-12-23 | 柳州一健科技有限公司 | Method for controlling driving unit of self-propelled engineering machinery |
| CN105160793B (en) * | 2015-09-01 | 2018-12-25 | 小米科技有限责任公司 | alarm method and device |
| CN105160793A (en) * | 2015-09-01 | 2015-12-16 | 小米科技有限责任公司 | Alarming method and apparatus |
| CN105611251A (en) * | 2015-12-30 | 2016-05-25 | 成都移动魔方科技有限公司 | Real time security monitoring method |
| CN106205143A (en) * | 2016-08-29 | 2016-12-07 | 苏州金螳螂怡和科技有限公司 | Intelligent bayonet networked system |
| CN106331629A (en) * | 2016-08-29 | 2017-01-11 | 合肥康胜达智能科技有限公司 | Safety monitoring system |
| CN106530711A (en) * | 2016-12-16 | 2017-03-22 | 合肥寰景信息技术有限公司 | Video image intelligent traffic analysis method for high-speed vehicle |
| CN107426009A (en) * | 2017-05-24 | 2017-12-01 | 上海三吉电子工程有限公司 | Subway communication network management system |
| CN107318039A (en) * | 2017-08-15 | 2017-11-03 | 龙岩龙安安全科技有限公司 | A kind of intelligent pop-up monitoring and warning system |
| CN107318039B (en) * | 2017-08-15 | 2023-03-24 | 龙岩龙安安全科技有限公司 | Intelligent popup window monitoring and warning system |
| CN109495718A (en) * | 2018-11-02 | 2019-03-19 | 深圳市北斗智能科技有限公司 | Monitor video acquisition methods, device and computer readable storage medium |
| CN109753893A (en) * | 2018-12-20 | 2019-05-14 | 广州航天海特系统工程有限公司 | Video detecting method, system, computer equipment and storage medium along track |
| CN113256924A (en) * | 2020-02-12 | 2021-08-13 | 中车唐山机车车辆有限公司 | Monitoring system, monitoring method and monitoring device for rail train |
| CN114463949A (en) * | 2022-02-07 | 2022-05-10 | 中铁大桥勘测设计院集团有限公司武汉分公司 | Station platform boundary-crossing alarm device of passenger station house |
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Application publication date: 20101215 |