CN102625083B - Method for constructing video monitoring network - Google Patents
Method for constructing video monitoring network Download PDFInfo
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- CN102625083B CN102625083B CN201210057725.5A CN201210057725A CN102625083B CN 102625083 B CN102625083 B CN 102625083B CN 201210057725 A CN201210057725 A CN 201210057725A CN 102625083 B CN102625083 B CN 102625083B
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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 refer to that especially a kind of probability occurring by statistical phenomeon improves the building method that improves overall network before relevant camera.
Background technology
At present, opportunity and the maturation of condition of social security video monitoring established and improve in nationwide.From technical conditions, video monitoring system technology is very ripe at present.From fund guarantee aspect, prefectures and cities are the completely capable funds that drop into also, and from the angle of being benefited, this input is worth completely.Situation about setting up at present from some national districts and cities of present contact, installs and social security video monitoring clipping the ball, the camera gun of some quantity of coming into operation are being brought into play certain effect aspect fighting crime.
But still there are the following problems in current building-up work: one, information-based isolated island phenomenon is serious, and very little, monitoring coverage rate is too little, and does not become system for built quantity, and benefit is not high; Two, lack standards system complete, science, the construction situation imbalance of each department, walk to be in advance in Some Cities And Towns; Three, built part lacks overall planning, and outstanding behaviours does not have specific aim in camera lens addressing, and system is not passed through rigorous demonstration, there is no unified technical standard, and dispersion seems; Four, be to lack suitable operation and management mode, administrative mechanism imperfection, lacks the professional talent and the training system safeguarded, lacks a set of complete daily operation management mechanism and shared mechanism.
Social security monitoring system front end camera Quantity is various now, invest huge, whether but camera is arranged reasonable, whether be all 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 is the major defect for conventional art.
Summary of the invention
The invention provides a kind of building method of video surveillance network, the camera that its method by science arranges in video surveillance network can reach the higher effect of reducining the construction costs of monitoring efficiency, and this is to be main purpose of the present invention.
The technical solution adopted in the present invention is: a kind of building method of video surveillance network, it comprises the steps:
The first step, at the preliminary video surveillance network of the monitored region division of needs, utilize this preliminary video surveillance network to carry out video information sampling to monitored region, this preliminary video surveillance network comprises some video frequency pick-up heads, some these video frequency pick-up heads are arranged in monitored region, thereby form this preliminary video surveillance network.
This video frequency pick-up head of each in second step, the first step is connected with memory by data transmission link, video information in the monitored region being collected by this video frequency pick-up head is stored in this memory through transfer of data, and by video analysis processor, the video information being stored in this memory is carried out to event video extraction.
The event video type that can need to be extracted out according to user's predefine setting when this video analysis processor carries out event video extraction to video information.
In concrete enforcement, this event video is the video information that includes public order incident, traffic events, fire-fighting event etc. content, public order incident more typically refers to that case is grabbed in pilferage case, robbery, retailer disorderly puts and sells case etc., traffic events more typically refers to break in traffic rules and regulations case, road traffic accident case of vehicle or pedestrian etc., and fire-fighting event more typically refers to fire floods case etc.
The method that this video analysis processor carries out event video extraction to video information can adopt various ways to carry out.
In concrete enforcement, in this video analysis processor, be provided with key element comparison storehouse, in this key element comparison storehouse, store the information that this event video must comprise that occurs.
Such as, the information of grabbing in this key element comparison storehouse of case corresponding to the robbery in public order incident can be set to cutter, rifle, club etc., can be set to vehicle corresponding to the information in this key element comparison storehouse of the road traffic accident case in traffic events and stop and exceed specific time etc. at non-parking area, can be set to occur fire, cigarette etc. corresponding to the information in this key element comparison storehouse of the fire case in fire-fighting event.
This video analysis processor is compared one by one by the video information in this key element comparison storehouse and this memory, and in the time including the information comprising in this key element comparison storehouse in video information, this video information is taken as event video and is extracted.
In this video analysis processor, be also provided with code library, 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.
Bind together and send to statistics to get server ready the event video extracting and the camera code of the video frequency pick-up head that photographs this event video.
The 3rd step, this statistics are got server ready and are connected with map server, in this map server, store the cartographic information that needs monitored region in the first step, this map server is got the advanced map information delivery in region monitored needs to this statistics in server ready, and this statistics is got the geographical coordinate that stores each this video frequency pick-up head in the first step in server ready.
This statistics is got server ready, first, each this video frequency pick-up head is identified at according to its geographical coordinate in the cartographic information that needs monitored region, then, this statistics is got server ready and is often received that this event video in a second step just gets mark ready corresponding to this video frequency pick-up head position that photographs this event video in the cartographic information in the monitored region of needs, finally, got ready the statistical graph of server maps outgoing event video probability of happening by this statistics.
The 4th step, according to the statistical graph of the event video probability of happening in the 3rd step, video surveillance network is built in the monitored region of the needs of personnel in the first step and is continued to increase video frequency pick-up head, thereby reaches according to the scientific and efficient object that video surveillance network is set of actual conditions.
Thereby the step repetitive cycling of the 5th step, the first step to the four steps carries out improving overall video surveillance network.
Beneficial effect of the present invention is: utilize the technical scheme of the present invention can be for the feature of public security complex region and case section occurred frequently dynamic translation, by the ratio between number of cameras and the incidence of criminal offenses number of analytic statistics system instant analysis specific region, generate video camera distribution density table, and using this as carrying out and mend some construction in low density regional organization with reference to foundation.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 for the benefit point of follow-up social security monitoring system, move a construction the more foundation of science be provided.
Accompanying drawing explanation
Fig. 1 is 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, at the preliminary video surveillance network of the monitored region division of needs, utilize this preliminary video surveillance network to carry out video information sampling to monitored region.
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 monitored region, thereby forms this preliminary video surveillance network.
This video frequency pick-up head 10 of each in second step, the first step is connected with memory 20 by data transmission link, video information in the monitored region being collected by this video frequency pick-up head 10 is stored in this memory 20 through transfer of data, and by video analysis processor 30, the video information being stored in this memory 20 is carried out to event video extraction.
The event video type that can need to be extracted out according to user's predefine setting when this video analysis processor 30 carries out event video extraction to video information.
In concrete enforcement, this event video is the video information that includes public order incident, traffic events, fire-fighting event etc. content.
Public order incident more typically refers to that case is grabbed in pilferage case, robbery, retailer disorderly puts and sells case etc.
Traffic events more typically refers to break in traffic rules and regulations case, road traffic accident case of vehicle or pedestrian etc.
Fire-fighting event more typically refers to fire floods case etc.
The method that this video analysis processor 30 carries out event video extraction to video information can adopt various ways to carry out.
In concrete enforcement, in this video analysis processor 30, be provided with key element comparison storehouse, in this key element comparison storehouse, store the information that this event video must comprise that occurs.
Such as, the information of grabbing in this key element comparison storehouse of case corresponding to the robbery in public order incident can be set to cutter, rifle, club etc.
Can be set to vehicle corresponding to the information in this key element comparison storehouse of the road traffic accident case in traffic events stops and exceedes specific time etc. at non-parking area.
Can be set to occur fire, cigarette etc. corresponding to the information in this key element comparison storehouse of the fire case in fire-fighting event.
This video analysis processor 30 is compared one by one by the video information in this key element comparison storehouse and this memory 20, in the time including the information comprising in this key element comparison storehouse in video information, this video information is taken as event video and is extracted.
In this video analysis processor 30, be also provided with code library, 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.
Bind together and send to statistics to get server 40 ready the event video extracting and the camera code of the video frequency pick-up head 10 that photographs this event video.
The 3rd step, this statistics are got server 40 ready and are connected with map server 50, in this map server 50, store the cartographic information that needs monitored region in the first step.
This map server 50 is got the advanced map information delivery in region monitored needs to this statistics in server 40 ready.
This statistics is got the geographical coordinate that stores each this video frequency pick-up head 10 in the first step in server 40 ready.
This statistics is got server 40 ready, first, each this video frequency pick-up head 10 is identified in the cartographic information that needs monitored region according to its geographical coordinate.
Then, this statistics is got server 40 ready and is often received that this event video in a second step just gets mark ready corresponding to these video frequency pick-up head 10 positions that photograph this event video in the cartographic information in the monitored region of needs.
Finally, get server 40 ready and draw out the statistical graph of event video probability of happening by this statistics.
The 4th step, according to the statistical graph of the event video probability of happening in the 3rd step, video surveillance network is built in the monitored region of the needs of personnel in the first step and is continued to increase video frequency pick-up head, thereby reaches according to the scientific and efficient object that video surveillance network is set of actual conditions.
Thereby the step repetitive cycling of the 5th step, the first step to the four steps carries out improving overall video surveillance network.
Claims (3)
1. a building method for video surveillance network, is characterized in that, comprises the steps:
The first step, at the preliminary video surveillance network of the monitored region division of needs, utilize this preliminary video surveillance network to carry out video information sampling to monitored region, this preliminary video surveillance network comprises some video frequency pick-up heads, some these video frequency pick-up heads are arranged in monitored region, thereby form this preliminary video surveillance network
This video frequency pick-up head of each in second step, the first step is connected with memory by data transmission link, video information in the monitored region being collected by this video frequency pick-up head is stored in this memory through transfer of data, and by video analysis processor, the video information being stored in this memory is carried out to event video extraction
In this video analysis processor, be provided with key element comparison storehouse, in this key element comparison storehouse, store the information that this event video must comprise that occurs, this video analysis processor is compared one by one by the video information in this key element comparison storehouse and this memory, in the time including the information comprising in this key element comparison storehouse in video information, this video information is taken as event video and is extracted
In this video analysis processor, be also provided with code library, camera code in this code library is corresponding one by one with this video frequency pick-up head in this preliminary video surveillance network, bind together and send to statistics to get server ready the event video extracting and the camera code of the video frequency pick-up head that photographs this event video
The 3rd step, this statistics are got server ready and are connected with map server, in this map server, store the cartographic information that needs monitored region in the first step, this map server is got the advanced map information delivery in region monitored needs to this statistics in server ready, this statistics is got the geographical coordinate that stores each this video frequency pick-up head in the first step in server ready
This statistics is got server ready, first, each this video frequency pick-up head is identified at according to its geographical coordinate in the cartographic information that needs monitored region, then, this statistics is got server ready and is often received that this event video in a second step just gets mark ready corresponding to this video frequency pick-up head position that photographs this event video in the cartographic information in the monitored region of needs, finally, got ready the statistical graph of server maps outgoing event video probability of happening by this statistics
The 4th step, according to the statistical graph of the event video probability of happening in the 3rd step, video surveillance network is built and in the monitored region of the needs of personnel in the first step, is continued to increase video frequency pick-up head.
2. the building method of a kind of video surveillance network as claimed in claim 1, is characterized in that: this event 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 comprise the 5th step, thereby the step repetitive cycling that the 5th step is the first step to the four steps carries out improving overall video surveillance network.
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| CN201210057725.5A CN102625083B (en) | 2012-03-07 | 2012-03-07 | Method for constructing video monitoring network |
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| CN201210057725.5A CN102625083B (en) | 2012-03-07 | 2012-03-07 | Method for constructing video monitoring network |
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| CN102625083B true CN102625083B (en) | 2014-05-28 |
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Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103079057B (en) * | 2012-12-29 | 2016-03-09 | 深圳先进技术研究院 | The method and system of resource optimization is carried out for video monitoring analytical 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 |
| 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 |
| CN109830117B (en) * | 2019-03-13 | 2021-07-30 | 百度国际科技（深圳）有限公司 | Road planning optimization 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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| CN201355495Y (en) * | 2008-12-05 | 2009-12-02 | 上海汇纳网络信息科技有限公司 | Mall passenger flow analysis system |
| CN201430657Y (en) * | 2009-04-23 | 2010-03-24 | 利津县公安局 | Public security network video monitoring system |
| CN201830395U (en) * | 2010-11-03 | 2011-05-11 | 西安先进视讯网络工程有限公司 | Oil well monitoring system |
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| CN101370128A (en) * | 2008-10-17 | 2009-02-18 | 北京中星微电子有限公司 | Intelligent video monitoring system |
| CN201355495Y (en) * | 2008-12-05 | 2009-12-02 | 上海汇纳网络信息科技有限公司 | Mall passenger flow analysis system |
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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. |