Stereo Context for Robust Object Tracking
Authors: 
Yating Xie, Da-Han Wang, Hanzi WangAuthors Info & Claims
Yating Xie, Da-Han Wang, Hanzi WangAuthors Info & ClaimsPages 125 - 129
Abstract
Context has been successfully applied to 2D image processing in the tasks of object detection, object recognition, etc. However, it is usually ignored in 3D object tracking. In this paper, we propose a stereo context-based object tracker that explores 3D context information for collaborative tracking in binocular video streams. The target is located by voting from companions, which are keypoints that have strong 3D motion correlations to the target. The companions are obtained by using spatial-temporal constraints in 3D space. Quantitative experimental results on challenging video sequences demonstrate the robustness and superior performance of the proposed tracker.
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Index Terms
- Stereo Context for Robust Object Tracking
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Information & Contributors
Information
Published In
July 2014
430 pages
ISBN:9781450328104
DOI:10.1145/2632856
- General Chairs:
- Hanzi Wang,
- Larry Davis,
- Program Chairs:
- Wenwu Zhu,
- Stephan Kopf,
- Yanyun Qu,
- Publications Chairs:
- Jun Yu,
- Jitao Sang,
- Tao Mei
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In-Cooperation
- NSF of China: National Natural Science Foundation of China
- Beijing ACM SIGMM Chapter
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 10 July 2014
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ICIMCS '14
ICIMCS '14: International Conference on Internet Multimedia Computing and Service
July 10 - 12, 2014
Xiamen, China
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Overall Acceptance Rate 163 of 456 submissions, 36%
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