The Research and Application of Visual Saliency and Adaptive Support Vector Machine in Target Tracking Field

Author:

Chen Yuantao12ORCID,Xu Weihong12,Kuang Fangjun13,Gao Shangbing1

Affiliation:

1. School of Computer Science and Engineering, Nanjing University of Science & Technology, Nanjing 210094, China

2. School of Computer and Communication Engineering, Changsha University of Science & Technology, Changsha 410114, China

3. Department of Computer Science and Technology, Hunan Vocational Institute of Safety & Technology, Changsha 410151, China

Abstract

The efficient target tracking algorithm researches have become current research focus of intelligent robots. The main problems of target tracking process in mobile robot face environmental uncertainty. They are very difficult to estimate the target states, illumination change, target shape changes, complex backgrounds, and other factors and all affect the occlusion in tracking robustness. To further improve the target tracking’s accuracy and reliability, we present a novel target tracking algorithm to use visual saliency and adaptive support vector machine (ASVM). Furthermore, the paper’s algorithm has been based on the mixture saliency of image features. These features include color, brightness, and sport feature. The execution process used visual saliency features and those common characteristics have been expressed as the target’s saliency. Numerous experiments demonstrate the effectiveness and timeliness of the proposed target tracking algorithm in video sequences where the target objects undergo large changes in pose, scale, and illumination.

Funder

Scientific Research Fund of Hunan Provincial Education Department

Publisher

Hindawi Limited

Subject

Applied Mathematics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,General Medicine

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