• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Robust human tracking via key face information

Vol. 10, No.10, October 31, 2016
10.3837/tiis.2016.10.026, Download Paper (Free):

Abstract

Tracking human body is an important problem in computer vision field. Tracking failures caused by occlusion can lead to wrong rectification of the target position. In this paper, a robust human tracking algorithm is proposed to address the problem of occlusion, rotation and improve the tracking accuracy. It is based on Tracking-Learning-Detection framework. The key auxiliary information is used in the framework which motivated by the fact that a tracking target is usually embedded in the context that provides useful information. First, face localization method is utilized to find key face location information. Second, the relative position relationship is established between the auxiliary information and the target location. With the relevant model, the key face information will get the current target position when a target has disappeared. Thus, the target can be stably tracked even when it is partially or fully occluded. Experiments are conducted in various challenging videos. In conjunction with online update, the results demonstrate that the proposed method outperforms the traditional TLD algorithm, and it has a relatively better tracking performance than other state-of-the-art methods.


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Cite this article

[IEEE Style]
Weisheng Li, Xinyi Li and Lifang Zhou, "Robust human tracking via key face information," KSII Transactions on Internet and Information Systems, vol. 10, no. 10, pp. 5112-5128, 2016. DOI: 10.3837/tiis.2016.10.026

[ACM Style]
Li, W., Li, X., and Zhou, L. 2016. Robust human tracking via key face information. KSII Transactions on Internet and Information Systems, 10, 10, (2016), 5112-5128. DOI: 10.3837/tiis.2016.10.026