Multi-target tracking method based on layered hypergraph optimization

Abstract

The invention discloses a multi-target tracking method. The multi-target tracking method comprises the steps that S1, a video is divided into time quanta in the time domain, target detection is carried out on each video frame, and the detection results serve as suspected target areas; S2, the positions of the suspected target areas obtained in the S1 serve as vertexes, otherwise, local tracks in the time quanta serve as vertexes, the relation between the local tracks serves as edges, and an affinity graph of the local tracks is built; S3, a plurality of intensive neighbor kinds are obtained from the affinity graph in a searching mode, and the local tracks belonging to the same intensive neighbor kind serve as local tracks belonging to the same target; S4, unit time quanta belonging to the same time quantum are aggregated to form a plurality of new unit time quanta, and local tracks, belonging to the same intensive neighbor kind, in the same new unit time quantum are merged to form a merging track; S5, whether a single time quantum has crossed the whole tracking time domain or not is judged, if yes, the merging track obtained at present serves as a tracking track of a monitored target, and if not, the S2 is executed.

Description

technical field [0001] The invention relates to the fields of image processing, pattern recognition and computer vision, in particular to a multi-target tracking method based on hierarchical hypergraph optimization. Background technique [0002] Multiple object tracking is an important but difficult problem in computer vision. Although existing tracking methods partially solve the tracking difficulties to varying degrees, their performance in practical applications is often unsatisfactory. Recently, due to the rapid development of object detection technology, multi-object tracking methods based on data association have gradually become mainstream. Given the object detection results of each frame of image, the multi-object tracking problem can be modeled as the process of associating multiple object detection results from different frames and forming a continuous trajectory. [0003] In practical applications, the relationship between multiple detection results across the t...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is that the current multi-target tracking method cannot deal with the long-term occlusion problem and cannot effectively identify similar-looking targets that are close to the spatial position

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