Method of realizing video target tracking by adopting two-layer cascading Boosting classification algorithm

Abstract

The invention discloses a method of realizing video target tracking by adopting a two-layer cascading Boosting classification algorithm. The method is characterized in that image pretreatment is used to acquire target samples and image blocks in target areas; characteristic values of positive samples and negative samples can be acquired by adopting characteristic extraction of filters; the two-layer Boosting cascading algorithm comprising the on-line characteristic selection and the weight training is provided; and a classifier is used to detect the target tracking. A plurality of filters are used for the characteristic extraction of the image blocks, and the characteristics of the image blocks can be expressed in a refined manner, and then the problems such as single template formed by adopting Haar-like characteristics, loss of image colors and texture details can be solved; and in addition, by adopting the two-layer cascading structure, the filter types and the image block positions can be selected respectively, and then the selected characteristics are more suitable for the tracking task.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a method for realizing video target tracking by using a two-layer cascaded Boosting classification algorithm. Background technique [0002] Video-based object tracking technology is a classic problem that many scholars in the field of computer vision and image processing pay attention to. With the rapid development of technologies such as computer storage, network communication, and image processing, video tracking technology has also made great progress. [0003] It is very challenging to design a stable and efficient target tracking algorithm. The difficulty mainly comes from the influence of factors such as complex background, target occlusion, and target deformation and rotation in the application. The current popular algorithms are mainly divided into two categories: generative and discriminative. The generation method uses the tracking target as a feature to constr...

AI Technical Summary

Problems solved by technology

Compared with the traditional method, the present invention uses multiple filters to extract features from the image block, expresses the features of the image block more finely, and solves the problem of using a Haar-like feature to construct a single template and losing image color and texture details; in addition , the proposed tracking method uses a two-layer cascaded structure to select the filter type and image block position separately, and make the selected features suitable for the tracking task as much as possible

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