Video detection generated background
(1) There are no unified management platforms for different monitoring networks such as safe cities, road monitoring, and social monitoring. The surveillance cameras are widely distributed, management is confusing, and image retrieval is difficult;
(2) The variety of video formats, the lack of a unified video index management and playback tools, resulting in low viewing efficiency, greatly limiting the use of video surveillance data efficiency and scope;
(3) The uneven quality of the video affects the accurate determination of suspected targets of the case officers.
(4) The manual viewing of the video takes time and effort, and the clues of the target are scattered. It is impossible to achieve effective clue matching and resource sharing, and it is easy to miss the suspect target and delay the fighter.
With the wide application of surveillance video in the * business, video detection technology that finds clues and traces suspect targets from video recordings has become the fourth largest technical means for detecting crimes after criminal technology, action technology, and cyber investigation technology. Detection plays an increasingly important role.
What is video surveillance?
Video investigation refers to the fact that the investigating agency, based on the needs of the case, uses the four steps of video surveillance data retrieval, viewing, analysis and application to realize dynamic analysis and comprehensive judgment of crimes, in order to discover and identify criminal suspects and find clues to solve crimes. An investigative measure that provides direction for case investigation.
The purpose of video investigation?
(1) Improve investigation efficiency (2) Improve investigation capability (3) Reduce labor intensity Application of video investigation (1) Video big data structured platform Thousands of video structured large data platform adopts advanced independent intellectual property rights deep learning algorithm With advanced big data technology, it can simultaneously structure and retrieve massive surveillance cameras, virtual bayonet, and human face video. The system uses high-density intelligent servers, which have high throughput, small footprint, seamless overlay, and smooth capacity expansion. A single cabinet can handle 480 HD video. It can be deployed separately to meet the applications of tagging and searching of massive videos, and can also be used as a core part of video intelligence processing in smart cities, safe cities, three-dimensional public security prevention and control, and triple play and other projects.
(1) Video Investigation Studio
Video reconnaissance studio composition
Thousands of thousands of video surveillance studio V3.0 is a set of "one-stop" solutions for the investigation of the case from video capture to intelligent analysis to case study. The program consists of video surveillance, case study, image processing and other business functions. Among them, video surveillance incorporates deep learning technology to accurately identify pedestrians, cars, people riding on two-wheeled vehicles, tricycles, and other targets based on the moving targets in the video, and structured the target to generate structured data, effectively improving traditional *videos. The investigation business depends on the situation of human-sea tactics to improve the efficiency of case detection.
(2) Multi-police Synthetic Combat Platform
Multi-alarm synthetic combat platform system architecture
Based on video surveillance, the "three vertical and one horizontal" multi-alarm synthetic combat platform is a video investigation full-chain solution. The system is highly integrated with map detection and combat platforms, vehicle inspection platforms, and case judgment platforms to create the whole process of cases and clues. Based on the self-developed human-vehicle classification and retrieval technology, deep learning technology, and video structuring technology, Qianshitong preprocesses massive amounts of data to lay a solid foundation for subsequent business applications. Through the synthetic combat network to achieve cross-human, cross-sector, cross-system and even cross-police online collaboration and communication.
(3) Video and Image Synthesis Judgment Platform
Video image synthesis and judgment platform function
The video and video comprehensive research and judgment platform of Chisight builds two sub-systems: "Personal Video Investigation" and "Video Image Analysis" to realize the whole process of video investigation work, link up with basic platform resources, and carry out video enrichment, retrieval, target snapshot, and clue synchronization. Video surveillance work; application of video structuring technology to extract features of people, vehicles, and objects; synergy analysis and judgment model for case depth analysis; and combining case, case, and graph search to find laws between cases and cases, realizing cases Concatenation.
With the continuous expansion of the scale of video surveillance, it also brings in a large amount of video data, which makes the traditional video cues based on human tactics look like a needle in a haystack. * Case investigation departments have become increasingly demanding in intelligence for various types of police analysis and video rapid analysis and retrieval. At present, the policing informatization method has shown its inability to deal with the situation and is facing the following severe challenges:
(1) There are no unified management platforms for different monitoring networks such as safe cities, road monitoring, and social monitoring. The surveillance cameras are widely distributed, management is confusing, and image retrieval is difficult;
(2) The variety of video formats, the lack of a unified video index management and playback tools, resulting in low viewing efficiency, greatly limiting the use of video surveillance data efficiency and scope;
(3) The uneven quality of the video affects the accurate determination of suspected targets of the case officers.
(4) The manual viewing of the video takes time and effort, and the clues of the target are scattered. It is impossible to achieve effective clue matching and resource sharing, and it is easy to miss the suspect target and delay the fighter.
With the wide application of surveillance video in the * business, video detection technology that finds clues and traces suspect targets from video recordings has become the fourth largest technical means for detecting crimes after criminal technology, action technology, and cyber investigation technology. Detection plays an increasingly important role.
What is video surveillance?
Video investigation refers to the fact that the investigating agency, based on the needs of the case, uses the four steps of video surveillance data retrieval, viewing, analysis and application to realize dynamic analysis and comprehensive judgment of crimes, in order to discover and identify criminal suspects and find clues to solve crimes. An investigative measure that provides direction for case investigation.
The purpose of video investigation?
(1) Improve investigation efficiency (2) Improve investigation capability (3) Reduce labor intensity Application of video investigation (1) Video big data structured platform Thousands of video structured large data platform adopts advanced independent intellectual property rights deep learning algorithm With advanced big data technology, it can simultaneously structure and retrieve massive surveillance cameras, virtual bayonet, and human face video. The system uses high-density intelligent servers, which have high throughput, small footprint, seamless overlay, and smooth capacity expansion. A single cabinet can handle 480 HD video. It can be deployed separately to meet the applications of tagging and searching of massive videos, and can also be used as a core part of video intelligence processing in smart cities, safe cities, three-dimensional public security prevention and control, and triple play and other projects.
(1) Video Investigation Studio
Video reconnaissance studio composition
Thousands of thousands of video surveillance studio V3.0 is a set of "one-stop" solutions for the investigation of the case from video capture to intelligent analysis to case study. The program consists of video surveillance, case study, image processing and other business functions. Among them, video surveillance incorporates deep learning technology to accurately identify pedestrians, cars, people riding on two-wheeled vehicles, tricycles, and other targets based on the moving targets in the video, and structured the target to generate structured data, effectively improving traditional *videos. The investigation business depends on the situation of human-sea tactics to improve the efficiency of case detection.
(2) Multi-police Synthetic Combat Platform
Multi-alarm synthetic combat platform system architecture
Based on video surveillance, the "three vertical and one horizontal" multi-alarm synthetic combat platform is a video investigation full-chain solution. The system is highly integrated with map detection and combat platforms, vehicle inspection platforms, and case judgment platforms to create the whole process of cases and clues. Based on the self-developed human-vehicle classification and retrieval technology, deep learning technology, and video structuring technology, Qianshitong preprocesses massive amounts of data to lay a solid foundation for subsequent business applications. Through the synthetic combat network to achieve cross-human, cross-sector, cross-system and even cross-police online collaboration and communication.
(3) Video and Image Synthesis Judgment Platform
Video image synthesis and judgment platform function
The video and video comprehensive research and judgment platform of Chisight builds two sub-systems: "Personal Video Investigation" and "Video Image Analysis" to realize the whole process of video investigation work, link up with basic platform resources, and carry out video enrichment, retrieval, target snapshot, and clue synchronization. Video surveillance work; application of video structuring technology to extract features of people, vehicles, and objects; synergy analysis and judgment model for case depth analysis; and combining case, case, and graph search to find laws between cases and cases, realizing cases Concatenation.
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