Citation

Chen Y, Xu W, Kuang F, Gao S. Comput. Math. Methods Med. 2013; 2013: 925341.

Affiliation

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

Copyright

(Copyright © 2013, Hindawi Publishing)

DOI

10.1155/2013/925341

PMID

24363779

PMCID

PMC3865687

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.

Language: en