Abstract
Aiming at the problem of person tracking for mobile robot in complex and dynamic environment, a multi-feature tracking strategy is proposed in this paper, by which the target can be determined based on the joint similarity. The joint similarity consists of motion model similarity, color histogram similarity and human HOG feature similarity. The tracking of target is realized by the method of joint likelihood data association. The above strategy can solve the problems such as similar color interference, target loss, and target occlusion. In addition, considering the lost target, a fast search strategy is proposed to search the target. Finally, the method is tested with the mobile robot. The experimental results show that the proposed method is robust and effective when the target is moving rapidly, and it can satisfy the real-time requirement of the system.
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Acknowledgment
The authors would like to acknowledge the valuable support of Natural Sciences Foundation (NNSF) of China (No. 61573100, No. 61573101).
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Fang, F., Qian, K., Zhou, B., Ma, X. (2017). Research and Implementation of Person Tracking Method Based on Multi-feature Fusion. In: Huang, Y., Wu, H., Liu, H., Yin, Z. (eds) Intelligent Robotics and Applications. ICIRA 2017. Lecture Notes in Computer Science(), vol 10464. Springer, Cham. https://doi.org/10.1007/978-3-319-65298-6_14
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DOI: https://doi.org/10.1007/978-3-319-65298-6_14
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