Paper
19 January 2009 Hybrid real-time tracking of non-rigid objects under occlusions
Author Affiliations +
Proceedings Volume 7252, Intelligent Robots and Computer Vision XXVI: Algorithms and Techniques; 72520F (2009) https://doi.org/10.1117/12.806150
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States
Abstract
A mean shift algorithm has gained special attention in recent years due to its simplicity to enable real-time tracking. However, the traditional mean shift tracking algorithm can fail to track target under occlusions. In this paper we propose a novel technique which alleviates the limitation of mean shift tracking. Our algorithm employs the Kalman filter to estimate the target dynamics information. Moreover, the proposed algorithm performs the background check process to calculate the similarity which expresses how similar to target the background is. We then find the exact target position combining the motion estimation by Kalman filter and the color based estimation by the mean shift algorithm based on the similarity value. Therefore, the proposed algorithm can robustly track targets under several types of occlusion, while the mean shift and mean shift-Kalman filter algorithms fail.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wonkyum Lee, Joohwan Chun, Byung In Choi, YuKyung Yang, and Sungho Kim "Hybrid real-time tracking of non-rigid objects under occlusions", Proc. SPIE 7252, Intelligent Robots and Computer Vision XXVI: Algorithms and Techniques, 72520F (19 January 2009); https://doi.org/10.1117/12.806150
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Filtering (signal processing)

Motion estimation

RGB color model

Optical tracking

Algorithm development

Reliability

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