CN102625083A - Method for constructing video monitoring network - Google Patents
Method for constructing video monitoring network Download PDFInfo
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- CN102625083A CN102625083A CN2012100577255A CN201210057725A CN102625083A CN 102625083 A CN102625083 A CN 102625083A CN 2012100577255 A CN2012100577255 A CN 2012100577255A CN 201210057725 A CN201210057725 A CN 201210057725A CN 102625083 A CN102625083 A CN 102625083A
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Abstract
The invention relates to a method for constructing a video monitoring network. The method comprises the following steps: 1) setting a primary video monitoring network in a to-be-monitored area; 2) performing event video extraction on video information by a video analyzing processor; 3) utilizing a statistic dotting server to perform dotting statistics on an electronic map of the monitored area according to the probability of event video occurrence, and drawing a statistic diagram of the probability of the event video occurrence; and 4) continuing to add video cameras in the to-be-monitored area in the step 1) by video monitoring network construction personnel according to the statistic diagram of the probability of the event video occurrence.
Description
Technical field
The present invention relates to a kind of building method of video network, thereby be meant that especially a kind of probability that before relevant camera, takes place through statistical phenomeon improves the building method that improves overall network.
Background technology
At present, to establish and improve opportunity and the condition of social security video monitoring ripe in the nationwide.See that from technical conditions the video monitoring system technology is very ripe at present.From the fund guarantee aspect, prefectures and cities are also capable fully to drop into the funds, and from the angle of being benefited, this input is to be worth fully.From the situation that some districts and cities in the whole nation of present contact set up at present, install and social security video monitoring clipping the ball, the camera gun of some quantity of coming into operation are being brought into play certain function aspect fighting crime.
But still there is following problem in present building-up work: one, information-based isolated island phenomenon is serious, the quantity of having built very little, the monitoring coverage rate is too little, and does not become system, benefit is not high; Two, the standards system of lack of complete, science, the construction situation of each department is uneven, and walk to be in advance in the part cities and towns; Three, built up part and lacked overall planning, outstanding behaviours does not have specific aim in the camera lens addressing, and rigorous demonstration is not passed through by system, does not have unified technical standard, and dispersion seems; Four, be to lack suitable operational management pattern, the administrative mechanism imperfection, what lack specialty safeguards the talent and training system, lacks complete daily operation management mechanism and the shared mechanism of a cover.
Social security monitoring system front end camera construction quantity is various now; Invest huge; Whether but camera is arranged reasonable; Whether all be distributed in public security focus, difficult point and significant points, can only rely on grass-roots work personnel's working experience and impression to arrange that monitoring effect is undesirable, and this be the major defect for conventional art.
Summary of the invention
The present invention provides a kind of building method of video surveillance network, and it can reach the higher effect of reducining the construction costs of monitoring efficiency through the camera that scientific methods is provided with in the video surveillance network, and this is to be main purpose of the present invention.
The technical scheme that the present invention adopted is: a kind of building method of video surveillance network, it comprises the steps:
The first step, preliminary video surveillance network is set in the monitored zone of needs; Utilize this preliminary video surveillance network that the video information sampling is carried out in monitored zone; This preliminary video surveillance network comprises some video frequency pick-up heads; Some these video frequency pick-up heads are arranged in the monitored zone, thereby form this preliminary video surveillance network.
Each this video frequency pick-up head in second step, the first step all is connected with memory through data transmission link; Video information in the monitored zone that is collected by this video frequency pick-up head is stored in this memory through transfer of data, and is carried out the incident video and extract being stored in video information in this memory by the video analysis processor.
This video analysis processor carries out when the incident video extracts the incident video type that needs are extracted out being set according to user's predefine to video information.
In practical implementation; This incident video is the video information that includes public order incident, traffic events, fire-fighting incident or the like content; Public order incident is meant that more typically case is grabbed in pilferage case, robbery, the random pendulum of retailer is sold case or the like; Traffic events more typically is meant break in traffic rules and regulations case, road traffic accident case of vehicle or pedestrian or the like, and the fire-fighting incident more typically is meant fire floods case or the like.
The method that this video analysis processor carries out the extraction of incident video to video information can adopt multiple mode to carry out.
In practical implementation, be provided with key element comparison storehouse in this video analysis processor, store the information that this incident video must comprise that takes place in this key element comparison storehouse.
Such as; The information of grabbing in this key element comparison storehouse of case corresponding to the robbery in the public order incident can be set to cutter, rifle, club or the like; Can be set to vehicle corresponding to the information in this key element comparison storehouse of the road traffic accident case in the traffic events and stop above specific time or the like, can be set to occur fire, cigarette or the like corresponding to the information in this key element comparison storehouse of the fire case in the fire-fighting incident at non-parking area.
This video analysis processor is compared with the video information in this memory through this key element comparison storehouse one by one, and when including this key element in the video information and compare the information that is comprised in storehouse, this video information then is taken as the incident video and is extracted out.
Also be provided with code library in this video analysis processor, the camera code in this code library is corresponding one by one with this video frequency pick-up head in this preliminary video surveillance network.
Incident video that extracts and the camera code that photographs the video frequency pick-up head of this incident video are bound together and send to statistics get server ready.
The 3rd step, this statistics are got server ready and are connected with map server; Store the cartographic information that needs monitored zone in the first step in this map server; This map server will need the cartographic information in monitored zone to transfer to this statistics to get ready in the server, and this statistics is got the geographical coordinate that stores each this video frequency pick-up head in the first step in the server ready.
This statistics is got server ready; At first; Each this video frequency pick-up head is identified at according to its geographical coordinate in the cartographic information in the monitored zone of needs, then, this statistics get ready server whenever receive one time second the step in this incident video just in the cartographic information in the monitored zone of needs, get mark ready corresponding to this video frequency pick-up head position that photographs this incident video; Finally, get the statistical graph of server maps outgoing event video probability of happening ready by this statistics.
The 4th step, according to the statistical graph of incident video probability of happening in the 3rd step; Video surveillance network is built in the monitored zone of the needs of personnel in the first step and is continued to increase video frequency pick-up head, thereby reaches the purpose that video surveillance network is set according to the actual conditions scientific and efficient.
Thereby the step repetitive cycling in the 5th step, four steps of the first step to the carries out improving whole video surveillance network.
Beneficial effect of the present invention is: utilize technical scheme of the present invention can be directed against the characteristics of public security complex region and case highway section occurred frequently dynamic translation; Through the number of cameras of analytic statistics system instant analysis specific region and the ratio between the incidence of criminal offenses number; Generate video camera distribution density table, and mend some construction according to carrying out as a reference in low density regional organization with this.Utilize technical scheme of the present invention to compare calculating to case distributing position and camera distributing position; Even can accurately calculate the case treating number of each camera, these data all be follow-up social security monitoring system the benefit point, move a construction more scientific basis be provided.
Description of drawings
Fig. 1 is a functional-block diagram of the present invention.
Embodiment
As shown in Figure 1, a kind of building method of video surveillance network comprises the steps:
The first step, preliminary video surveillance network is set, utilizes this preliminary video surveillance network that the video information sampling is carried out in monitored zone in the monitored zone of needs.
This preliminary video surveillance network comprises some video frequency pick-up heads 10, and some these video frequency pick-up heads 10 are arranged in the monitored zone, thereby forms this preliminary video surveillance network.
Each this video frequency pick-up head 10 in second step, the first step all is connected with memory 20 through data transmission link; Video information in the monitored zone that is collected by this video frequency pick-up head 10 is stored in this memory 20 through transfer of data, and is stored in video information in this memory 20 by 30 pairs of video analysis processors and carries out the incident video and extract.
30 pairs of video informations of this video analysis processor carry out when the incident video extracts the incident video type that needs are extracted out being set according to user's predefine.
In practical implementation, this incident video is the video information that includes public order incident, traffic events, fire-fighting incident or the like content.
Public order incident is meant that more typically case is grabbed in pilferage case, robbery, the random pendulum of retailer is sold case or the like.
Traffic events more typically is meant break in traffic rules and regulations case, road traffic accident case of vehicle or pedestrian or the like.
The fire-fighting incident more typically is meant fire floods case or the like.
The method that 30 pairs of video informations of this video analysis processor are carried out the extraction of incident video can adopt multiple mode to carry out.
In practical implementation, be provided with key element comparison storehouse in this video analysis processor 30, store the information that this incident video must comprise that takes place in this key element comparison storehouse.
Such as, the information of grabbing in this key element comparison storehouse of case corresponding to the robbery in the public order incident can be set to cutter, rifle, club or the like.
Can be set to vehicle corresponding to the information in this key element comparison storehouse of the road traffic accident case in the traffic events stops above specific time or the like at non-parking area.
Information corresponding in this key element comparison storehouse of the fire case in the fire-fighting incident can be set to occur fire, cigarette or the like.
This video analysis processor 30 is compared through the video information in this key element comparison storehouse and this memory 20 one by one; In the time of the information that in including this key element comparison storehouse in the video information, comprised, this video information then is taken as the incident video and is extracted out.
Also be provided with code library in this video analysis processor 30, the camera code in this code library is corresponding one by one with this video frequency pick-up head 10 in this preliminary video surveillance network.
Incident video that extracts and the camera code that photographs the video frequency pick-up head 10 of this incident video are bound together and send to statistics get server 40 ready.
The 3rd step, this statistics are got server 40 ready and are connected with map server 50, store the cartographic information that needs monitored zone in the first step in this map server 50.
This map server 50 will need the cartographic information in monitored zone to transfer to this statistics to get ready in the server 40.
This statistics is got the geographical coordinate that stores each this video frequency pick-up head 10 in the first step in the server 40 ready.
This statistics is got server 40 ready, at first, each this video frequency pick-up head 10 is identified in the cartographic information in the monitored zone of needs according to its geographical coordinate.
Then, this statistics get ready server 40 whenever receive one time second the step in this incident video just in the cartographic information in the monitored zone of needs, get mark ready corresponding to these video frequency pick-up head 10 positions that photograph this incident video.
Finally, get the statistical graph that server 40 is drawn out incident video probability of happening ready by this statistics.
The 4th step, according to the statistical graph of incident video probability of happening in the 3rd step; Video surveillance network is built in the monitored zone of the needs of personnel in the first step and is continued to increase video frequency pick-up head, thereby reaches the purpose that video surveillance network is set according to the actual conditions scientific and efficient.
Thereby the step repetitive cycling in the 5th step, four steps of the first step to the carries out improving whole video surveillance network.
Claims (3)
1. the building method of a video surveillance network is characterized in that, comprises the steps:
The first step, preliminary video surveillance network is set in the monitored zone of needs; Utilize this preliminary video surveillance network that the video information sampling is carried out in monitored zone; This preliminary video surveillance network comprises some video frequency pick-up heads; Some these video frequency pick-up heads are arranged in the monitored zone, thereby form this preliminary video surveillance network
Each this video frequency pick-up head in second step, the first step all is connected with memory through data transmission link; Video information in the monitored zone that is collected by this video frequency pick-up head is stored in this memory through transfer of data; And carry out the incident video and extract being stored in video information in this memory by the video analysis processor
Be provided with key element comparison storehouse in this video analysis processor; Store the information that this incident video must comprise that takes place in this key element comparison storehouse; This video analysis processor is compared through the video information in this key element comparison storehouse and this memory one by one; In the time of the information that in including this key element comparison storehouse in the video information, comprised, this video information then is taken as the incident video and is extracted out
Also be provided with code library in this video analysis processor; Camera code in this code library is corresponding one by one with this video frequency pick-up head in this preliminary video surveillance network; Incident video that extracts and the camera code that photographs the video frequency pick-up head of this incident video are bound together and send to statistics get server ready
The 3rd step, this statistics are got server ready and are connected with map server; Store the cartographic information that needs monitored zone in the first step in this map server; This map server will need the cartographic information in monitored zone to transfer to this statistics to get ready in the server; This statistics is got the geographical coordinate that stores each this video frequency pick-up head in the first step in the server ready
This statistics is got server ready; At first, be identified at each this video frequency pick-up head in the cartographic information in the monitored zone of needs, then according to its geographical coordinate; This statistics get ready server whenever receive one time second the step in this incident video just in the cartographic information in the monitored zone of needs, get mark ready corresponding to this video frequency pick-up head position that photographs this incident video; Finally, get the statistical graph of server maps outgoing event video probability of happening ready by this statistics
The 4th step, according to the statistical graph of incident video probability of happening in the 3rd step, video surveillance network is built and is continued to increase video frequency pick-up head in the monitored zone of the needs of personnel in the first step.
2. the building method of a kind of video surveillance network as claimed in claim 1, it is characterized in that: this incident video is the video information that includes public order incident or traffic events or fire-fighting event content.
3. the building method of a kind of video surveillance network as claimed in claim 1 is characterized in that: also comprised for the 5th step, thereby the 5th step carried out improving whole video surveillance network for the step repetitive cycling in four steps of the first step to the.
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| CN201210057725.5A CN102625083B (en) | 2012-03-07 | 2012-03-07 | Method for constructing video monitoring network |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103079057A (en) * | 2012-12-29 | 2013-05-01 | 深圳先进技术研究院 | Method and system for resource optimization of video monitoring analysis system |
| CN104952253A (en) * | 2015-06-30 | 2015-09-30 | 公安部第三研究所 | Traffic violation behavior recording and early warning system and method |
| CN106448161A (en) * | 2016-09-30 | 2017-02-22 | 广东中星微电子有限公司 | Road monitoring method and road monitoring device |
| CN108510693A (en) * | 2018-05-30 | 2018-09-07 | 贵州民族大学 | A kind of Internet of Things fire-fighting system based on big data |
| CN108897028A (en) * | 2018-05-11 | 2018-11-27 | 星络科技有限公司 | Target object localization method, device, electronic equipment and readable storage medium storing program for executing |
| CN109830117A (en) * | 2019-03-13 | 2019-05-31 | 百度国际科技（深圳）有限公司 | Roading optimization method, device, computer equipment and storage medium |
| CN112601049A (en) * | 2020-12-08 | 2021-04-02 | 北京精英路通科技有限公司 | Video monitoring method and device, computer equipment and storage medium |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103079057A (en) * | 2012-12-29 | 2013-05-01 | 深圳先进技术研究院 | Method and system for resource optimization of video monitoring analysis system |
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| CN104952253A (en) * | 2015-06-30 | 2015-09-30 | 公安部第三研究所 | Traffic violation behavior recording and early warning system and method |
| CN106448161A (en) * | 2016-09-30 | 2017-02-22 | 广东中星微电子有限公司 | Road monitoring method and road monitoring device |
| CN108897028A (en) * | 2018-05-11 | 2018-11-27 | 星络科技有限公司 | Target object localization method, device, electronic equipment and readable storage medium storing program for executing |
| CN108510693A (en) * | 2018-05-30 | 2018-09-07 | 贵州民族大学 | A kind of Internet of Things fire-fighting system based on big data |
| CN109830117A (en) * | 2019-03-13 | 2019-05-31 | 百度国际科技（深圳）有限公司 | Roading optimization method, device, computer equipment and storage medium |
| CN112601049A (en) * | 2020-12-08 | 2021-04-02 | 北京精英路通科技有限公司 | Video monitoring method and device, computer equipment and storage medium |
| CN112601049B (en) * | 2020-12-08 | 2023-07-25 | 北京精英路通科技有限公司 | Video monitoring method and device, computer equipment and storage medium |
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| CN102625083B (en) | 2014-05-28 |
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Address after: 518000 4th floor, modern building, South 4th Road, Gaoxin, Nanshan District, Shenzhen City, Guangdong Province Patentee after: Shenzhen Radio & TV Xinyi Technology Co.,Ltd. Address before: 518000 4th floor, modern building, South 4th Road, Gaoxin, Nanshan District, Shenzhen City, Guangdong Province Patentee before: SHENZHEN XINYI TECHNOLOGY Co.,Ltd. |