Adaptive Probabilistic Tracking with Discriminative Feature Selection for Mobile Robot
Wang, Peng1; Luo, Yongkang1; Li, Wanyi1; Qiao, Hong2
2016-10
会议日期October 9-12, 2016
会议地点Budapest
关键词Object Tracking Mobile Robot Discrinimative Feature Selection
英文摘要Object tracking is one of the important tasks for mo- bile robot, and developing a robust and real-time visual tracking algorithm which can adaptively capture the varying appearance of target under challenging conditions for mobile robot is still an open problem. The main challenges of visual tracking for mobile robot come from variation of target's appearance and disturbance of environment. To cope with these problems, one of the most important topics is how to select the best tracking features. In this paper, we propose a novel adaptive probabilistic tracking method with discriminative feature selection for mobile robot. Different from the existing adaptive tracking algorithms which select the discriminative features in a finite feature set, the proposed method treats feature selection as an estimation problem of the best feature tunable parameters in a continuous space. The estimation of the best tunable parameters and object tracking are implemented via different particle filters with novel observation models. A novel target model updating strategy is also proposed to adapt to the varying appearance of target and resist gradual drift. Experiments show the robustness of the proposed method under challenging conditions.
会议录IEEE Ineternational Conference on Systems, Man, and Cybernetics
语种英语
内容类型会议论文
源URL[http://ir.ia.ac.cn/handle/173211/12114]  
专题精密感知与控制研究中心_精密感知与控制
通讯作者Li, Wanyi
作者单位1.Research Center of Precision Sensing and Control, Institute of Automation, Chinese Academy of Sciences
2.The State Key Lab of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences
3.CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT)
推荐引用方式
GB/T 7714
Wang, Peng,Luo, Yongkang,Li, Wanyi,et al. Adaptive Probabilistic Tracking with Discriminative Feature Selection for Mobile Robot[C]. 见:. Budapest. October 9-12, 2016.
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