CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
Real-time Depth-based Tracking Using A Binocular Camera
Zhang, Leijie; Cao, Zhiqiang; Meng, Xiangrui; Zhou, Chao; Wang, Shuo
2016-06
Conference NameWorld Congress on Intelligent Control and Automation(WCICA)
Conference DateJune 12-15, 2016
Conference PlaceGuilin, China
AbstractDepth map provides rich information and it can be utilized in object tracking to handle some challenging problems in conventional RGB tracking such as occlusions and model drift. In this paper, we present a tracker that provides an effective real-time target tracking method based on a binocular camera. The proposed tracker is an extension of the popular KCF algorithm that leverages a circulant structure of tracking-by-detection with kernels for tracking. On this basis, we design a simple yet effective method to detect occlusions and recover tracking using noisy depth map obtained from a binocular camera. Firstly, one needs to identify exact and reasonable peak number of the target region’s depth histogram and apply GMM model to evaluate the depth distribution. The occlusion is then detected based on the depth evaluation and the maximum response from KCF. When the occlusion happens, it is segmented to build the corresponding search region for recovery. The experimental results demonstrate the effectiveness of the proposed method and the superiority to the KCF tracker.
DOI10.1109/WCICA.2016.7578274
Citation statistics
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14798
Collection复杂系统管理与控制国家重点实验室_先进机器人
Corresponding AuthorCao, Zhiqiang
AffiliationState Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhang, Leijie,Cao, Zhiqiang,Meng, Xiangrui,et al. Real-time Depth-based Tracking Using A Binocular Camera[C],2016.
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