June 01, 2023

For meaningful monitoring, reduce massive video data.

For meaningful monitoring, reduce massive video data.

Society is rapidly developing, in order to ensure social order and quality of life of people around us, more and more surveillance cameras appear around us. However, we do not have ability to view all images. How can you see everything when you're too dizzy?

For meaningful monitoring, reduce massive video data.

Spying is said to be police's magic weapon for solving crimes. Indeed, evidence for solving crimes is objective and convincing. Today, police crime-solving capabilities have gradually evolved from initial visits and investigations to use of surveillance video to assist in solving cases, and some cases can even be solved by observing entire process.

However, image search technology is not as simple as observation observation, it requires strong logical thinking. Often, video surveillance involved in a case contains long-term video information from several or even dozens of cameras, and key observations at critical moments need to be compared many times. Hundreds of hours of video surveillance processing is no small project.

Similar to police investigation and case detection, perimeter protection, target tracking, equipment anomaly detection, passenger and cargo flow statistics, traffic accident monitoring, etc., all require extraction of key monitoring information, which includes a huge number of transactions. data is definitely a problem.

The core technology of intelligent video analysis is a video analysis algorithm based on background modeling and fuzzy recognition. The core technologies are accurate and fast target identification, implementation of predefined intelligent analysis functions, and reduction of false and missed alarms. At present, chip mainly meets needs of most intelligent analysis. For some complex algorithms, more manufacturers implement them on back end, such as search after video.

For meaningful monitoring, reduce massive video data.

Video enrichment extraction technology mainly uses image processing (including video enrichment, summary, recovery, etc.), pattern recognition, heavily classified data storage, and search technologies to analyze and extract video from storage and other raw information. Three categories of information content, target features, target behavior and inter-target relationships, form a variety of classified feature information databases, metadata and indexes, and provide a unified interface for external search applications to get to point with limited prompts. association and positioning.

Introducing intelligent video search technology can greatly improve search efficiency and hit rate of original mass surveillance video storage system. With development of high-definition technology and intelligent security, application of intelligent video search technology will become even brighter. However, due to complexity of this technology, promotion and popularization is still not enough to fill huge gap in market. I believe that in surveillance revolution, the rapid extraction of key surveillance data can definitely take video surveillance to a new level.

Related