A video multiple-target tracking method and device

Abstract

The present invention discloses a video multiple-target tracking method and device. The method includes: when a position box of a tracking target is included in a tracking result of a previous frame, regarding the previous frame, performing: distributing dense grids on the whole image, each of which corresponds to a feature point; determining a tracking feature point corresponding to the position box of each tracking target regarding the position boxes of all tracking targets, and recording a corresponding relation and a position of each tracking feature point; calculating position information of each tracking feature point in the current frame according to the position of each tracking feature point in the previous frame; generating and respectively storing the position box of each tracking target in the current frame according to the calculated position information of each tracking feature point in the current frame and the recorded corresponding relation of the previous frame; and determining the next frame of the video data as the current frame after outputting the tracking result, and performing the abovementioned process recurrently to achieve multiple-target tracking. Through application of the present invention, processing efficiency and accuracy can be greatly increased.

Description

technical field [0001] The invention relates to video monitoring technology, in particular to a method and device for video multi-target tracking. Background technique [0002] With the continuous advancement of smart city construction, a large-scale video surveillance network in the national sense has been initially formed. At the same time, one of the most direct consequences of the popularization of large-scale video surveillance networks is the generation of massive video data. Massive video data poses a huge challenge to traditional intelligent video analysis techniques. [0003] A very important task in intelligent video analysis is dynamic target capture and tracking, and many very important applications such as video retrieval, target recognition, behavior analysis, and video enrichment require the use of multi-target tracking technology. [0004] Existing multi-target tracking technologies can usually be divided into two categories: The first type of method is a d...

AI Technical Summary

Problems solved by technology

At present, the algorithm for processing multiple targets as a whole is relatively complex and the processing speed is slow

[0006] Because there are a lot of repeated calculations in the first type of method, and the second type of method has high computational complexity and slow processing speed, so these two types of methods are difficult to be practically applied in engineering

In addition, due to the complex movement of real-world targets, existing tracking methods usually lack the ability to select effective tracking features to balance tracking stability and accuracy.

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