Target tracking method with temporal and spatial context information combined

Abstract

The invention belongs to the field of pattern recognition and computer vision and discloses a target tracking method with temporal and spatial context information combined. The method comprises steps: a first frame of picture is used to train an initial strong classifier, and a temporal and spatial context model needed by next-frame tracking is learnt; when a new frame arrives, the well-trained strong classifier is used to estimate a plurality of blocks in a search area, and a first confidence matrix is obtained; the temporal and spatial context information is then integrated to obtain a confidence graph function, the function is used to solve the confidence value of each block in the search area, and a second confidence matrix is obtained; and finally, according to corresponding weight linear combination, a final confidence matrix is obtained, and a block with the maximum confidence value in the final confidence matrix is found to be the tracked target. Through combining the temporal and spatial context information of the target to an online Boosting algorithm, quick robust tracking can be realized.

Description

technical field [0001] The invention belongs to the technical fields of pattern recognition and computer vision, and in particular relates to a target tracking method combined with spatio-temporal context information. Background technique [0002] Moving object tracking is one of the important research directions in the field of computer vision, and has important applications in human-computer interaction, intelligent monitoring, medical imaging and other fields. Tracking algorithms have made great progress in recent years, but how to effectively solve the problem of tracking drift caused by occlusion, fast motion, illumination changes, background clutter and other factors is still a very challenging problem. [0003] The online Boosting algorithm, when a new frame arrives, uses a strong classifier to classify the background and target in the picture to obtain the target area, but when the target is occluded, it will use the occluded feature to update the feature pool, Poll...

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Problems solved by technology

[0007] In view of the shortcomings of the above-mentioned prior art, the purpose of the present invention is to provide a target tracking method combined with spatio-temporal context information, which can solve the tracking drift that occurs when the target area is partially occluded or the target scale changes greatly in the prior art. question

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