Abstract

It is difficult for a single-feature tracking algorithm to achieve strong robustness under a complex environment. To solve this problem, we proposed a multifeature fusion tracking algorithm that is based on game theory. By focusing on color and texture features as two gamers, this algorithm accomplishes tracking by using a mean shift iterative formula to search for the Nash equilibrium of the game. The contribution of different features is always keeping the state of optical balance, so that the algorithm can fully take advantage of feature fusion. According to the experiment results, this algorithm proves to possess good performance, especially under the condition of scene variation, target occlusion, and similar interference.

© 2017 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
Robust object tracking based on local discriminative sparse representation

Xin Wang, Siqiu Shen, Chen Ning, Yuzhen Zhang, and Guofang Lv
J. Opt. Soc. Am. A 34(4) 533-544 (2017)

Object tracking based on incremental Bi-2DPCA learning with sparse structure

Bendu Bai, Ying Li, Jiulun Fan, Chris Price, and Qiang Shen
Appl. Opt. 54(10) 2897-2907 (2015)

Oversaturated part-based visual tracking via spatio-temporal context learning

Wei Liu, Jicheng Li, Zhiguang Shi, Xiaotian Chen, and Xiao Chen
Appl. Opt. 55(25) 6960-6968 (2016)

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Figures (8)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Tables (3)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Equations (15)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Metrics

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription