A Fast Video Retrieval Method Based on Hierarchical and Structured Description of Video Information

Abstract

The invention provides a rapid video retrieval method based on layered structuralized description of video information, which is characterized in that based on graded video content of three databases and three engines, a comprehensive application framework and a research and judging flow are subjected to layered structuralized description, wherein the comprehensive application framework is that in a video monitoring network system, a plurality of nodes are deployed by layers according to an actual condition of each sub-network; and each node takes a video layered structuralized description server as a core and comprises complete three databases and three engines. The rapid video retrieval method based on the layered structuralized description of the video information has the advantages that the cooperative work of the three databases and the three engines with many grades and many nodes is utilized to carry out full-automatic layered structuralized description on monitoring video content; and logical reasoning and judgment are carried out based on a topological relation between the nodes, so as to realize intelligent research and judgment of the video monitoring information and realize automatic alarming and rapid retrieval.

Description

technical field [0001] The invention relates to a fast video retrieval method based on the layered and structured description of video information, which belongs to the field of security video monitoring. Background technique [0002] With the development of the economy and society, and the continuous improvement of people's demand for security, video surveillance systems have been rapidly developed and popularized in the past few decades. From the original single key security industries such as government agencies, road traffic, Financial institutions, etc., are gradually applied to more and more public facilities such as office buildings, shopping malls, residential quarters, etc. [0003] Social security monitoring produces a large amount of video information. However, most of the video information has nothing to do with solving the case. Useful information is mixed with a large amount of useless information, which prolongs the search cycle and delays the time to solve th...

AI Technical Summary

Problems solved by technology

[0009] However, in the above-mentioned prior art, even if part of the automatic analysis or automatic alarm function is realized, it is limited to separately analyzing the data collected by each camera terminal to form structured description information for query; The data of the camera terminal is comprehensively analyzed, without considering the rapid query and cross-retrieval of video content in the case of multiple video surveillance sub-networks and massive video information

In the face of the needs of police ultra-large-scale networked video surveillance systems or cross-provincial and cross-regional networked video surveillance systems, existing technologies are unable to meet the performance requirements of such ultra-large-scale systems

[0010] In addition, according to the video monitoring function module or network server of the prior art, it mainly faces a simple monitoring environment or a simple video monitoring network, and the analysis and retrieval of video information are limited to objects in a single video source / a few video sources For reasoning, judging, analyzing and storing, there is no mention of the method of realizing cross-network intelligent video monitoring through information interaction between sub-network nodes and logical reasoning through sub-network node topology between multiple video surveillance sub-networks. It also does not mention the hierarchical and structured description of video content across multiple sub-networks and the distributed and fast query method of video content

In the face of complex multiple sub-network integration systems, the above-mentioned prior art should not affect the respective video surveillance and alarm functions of the units, and at the same time satisfy the centralized video surveillance intelligent discrimination and alarm function, the permission setting will be very difficult, and the system The efficiency is not high, and there will be limitations in the requirement of being able to flexibly expand or disconnect a node

Therefore, the above patents still cannot meet the needs of police large-scale cross-regional level video surveillance intelligent analysis system

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