Video structured processing method based on target behavior attributes and video structured processing system based on target behavior attributes and storage device

Abstract

The invention discloses a video structured processing method based on target behavior attributes. The method comprises the steps that the basic attributes of the target are acquired by using a YOLO target detection algorithm; the trajectory information of the detected target is acquired by using a multi-target tracking algorithm; abnormal video frames are extracted by using an abnormal behavior analysis algorithm based on the motion light flow characteristics; the corresponding target category attributes and the target trajectories and other characteristic information are acquired by using themethod according to the meta-data structure constructed by customization; the false detection data existing in the extracted meta-data are corrected by using a weighted judgment method; and the acquired data are uploaded to the rear-end server to be further processed. With application of the mode, the unstructured video data can be converted into the structured data having practical value so thatthe network transmission efficiency of the video monitoring system can be enhanced and the load rate of the rear-end server can be reduced. The invention also provides a real-time processing system based on the target behavior attributes and a real-time processing device based on the target behavior attributes.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a video structure processing method, system and storage device based on target behavior attributes. Background technique [0002] With the development of intelligent monitoring technology, the processing of video is particularly important. In the prior art, the method of image feature detection is often used for video processing, but since the dimensionality of the video will be very high, and there will be a large number of redundant features and irrelevant features, this will cause the pressure of video processing and cannot be realized. The video is processed quickly, and the accuracy of obtaining target features will be reduced. Therefore, in order to meet the needs of the development of intelligent monitoring technology, a video processing method and a video processing system with high real-time performance and high accuracy are required. Contents of the invention [0003]...

AI Technical Summary

Problems solved by technology

In the prior art, the method of image feature detection is often used for video processing, but because the dimensionality in the video will be very high, and there will be a large number of redundant features and irrelevant features, which will cause the pressure of video processing and cannot be realized. Fast video processing, and will reduce the accuracy of acquiring target features

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