Tracking method based on integral and partial recognition of object

Abstract

The invention discloses a tracking method based on integral and partial recognition of an object. As for recognition based on partial information, superpixel division is conducted on all candidate areas, different weight values are given to superpixels according to characteristics of partial representation of the object, weighting similarity measurement is put forward, and the confidence coefficients of all the candidate target areas are calculated. As for recognition based on integrality, object property measurement is introduced into a target object detection portion of a current frame, colors, edges and the superpixels are chosen to serve as three types of clues of object property measurement, marking rules of the clues are provided respectively, the confidence coefficients are calculated by combining the three types of clues and recognition based on the partial information so as to mark all the candidate target areas in an extension area, and a target area is determined according to marks. According to the tracing method, the target object in a tracking scene dynamically changing can be described preferably, the target area is converged in the target object better by combing object property measurement, the probability of a background existing in the target are is reduced, and the tracking accuracy rate and tracking stability are improved.

Description

technical field [0001] The present invention relates to the field of computer vision, and more specifically, relates to a tracking method based on object integrity and locality recognition. Background technique [0002] Object tracking is an important research content in the field of computer vision, which has attracted widespread attention in recent years and has become a current research hotspot. This technology has broad application prospects and plays an important role in many fields, such as security monitoring, human-computer interaction, medical diagnosis and vehicle flow monitoring and so on. Although people have proposed a large number of object tracking methods, these methods often cannot provide ideal tracking results and cannot track the target object when the illumination and object shape change greatly or there is serious occlusion. Therefore, proposing an effective object tracking method has important application value and practical significance. [0003] Cu...

AI Technical Summary

Problems solved by technology

The recognition method based on local information has a good tracking effect in the case of partial occlusion or non-rigid changes in the target object. However, the lack of overall recognition of the target object may easily lead to deviation and only recognize part of the target object.

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