TLD and KCF fused video target tracking method

Abstract

The invention discloses a TLD and KCF fused video target tracking method. The method comprises the following steps that the position and size of a target area in an initial target frame are determined, and the initial frame is input to a TLD algorithm module and a KCF algorithm module; the TLD algorithm module and the KCF algorithm module run in parallel, and if only one of the TLD algorithm module and the KCF algorithm module processing a present frame includes tracking object output, the output serves as a tracking result of the present frame; and if both modules include tracking object output, the similarities St and Sk between the tracking object output and a target model M are calculated, and a maximum between the St and Sk is selected as a target tracking result; and the method is used to process a next frame of video till tracking of the video frames ends. According to the method, the disadvantage when the TLD and KCF algorithms are used independently can be overcome, the methodis widely adapted to target tracking of a complex video scene, and the instantaneity of the target tracking algorithms is maintained.

Description

technical field [0001] The invention relates to the technical field of video image processing methods, in particular to a video target tracking method combining TLD and KCF. Background technique [0002] Target tracking is the process of continuously obtaining the motion state of the target in the video sequence when the prior information of the target is known. It is one of the challenging research difficulties in the field of computer vision and has been widely used in various defense and civilian applications Fields, such as intelligent monitoring, human-computer interaction, medical diagnosis, navigation guidance, etc. Although a lot of research results have been achieved in video tracking technology in recent years, robust visual tracking is still a great challenge. The difficulties of video tracking mainly lie in the difficulty of accurately expressing target templates, complex target motion patterns, target deformation and scale changes, target occlusion and backgrou...

AI Technical Summary

Problems solved by technology

[0005] Although the TLD algorithm and the KCF algorithm have achieved good results in the tests of multiple video data sets, there are still obvious shortcomings when they are applied to the target tracking of actual complex scenes.

For example, the stability of the tracker of the TLD algorithm is not high, and it is easy to fail to track when there is complex background interference

The KCF algorithm cannot handle the situation where the target is occluded and the target is deformed.

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