Target tracking method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a target tracking method. The method comprises the following steps: extracting target counting information, target detection frame information and target prediction frame information of each frame of image in a to-be-processed image sequence; calculating a first tracking trajectory of each target in the to-be-processed image sequence; judging whether a first missing detection condition exists or not; if the first missing detection condition exists, judging whether a second missing detection condition exists or not according to the target prediction frame information corresponding to the nth frame of image and the first missing detection target point corresponding to the (n + 1) th frame of image; if the second missing detection condition does not exist, determining first missing detection frame information according to the first missing detection target point; if the second leak detection condition exists, determining second leak detection frame information according to the second leak detection target point; and obtaining a target tracking trajectory based on the first tracking trajectory, the first missing detection frame information and/or the second missing detection frame information. The accuracy of multi-target tracking can be improved.

Description

technical field [0001] The present invention relates to the field of artificial intelligence, in particular to a target tracking method, device, electronic equipment and storage medium. Background technique [0002] The multi-target tracking algorithm is an indispensable algorithm in smart cameras. A robust and high-precision multi-target tracking algorithm can greatly improve the performance of the entire smart video surveillance system. The multi-target tracking algorithm includes the target detection algorithm and the target ID matching tracking algorithm. Although there are multiple target tracking networks at present, for the target detection algorithm, in some cases, the target will be missed. For example, in a real scene, when the target is occluded or disturbed, especially in a crowded scene, the missed detection rate is high, resulting in a low target tracking accuracy. Therefore, the existing target tracking algorithms have the problem of low target detection accu...

AI Technical Summary

Problems solved by technology

The multi-target tracking algorithm includes the target detection algorithm and the target ID matching tracking algorithm. Although there are currently multiple target tracking networks, for the target detection algorithm, in some cases, the target will be missed.

For exam

Images