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http://dx.doi.org/10.9717/kmms.2016.19.5.865

Rotation Invariant Tracking-Learning-Detection System  

Choi, Wonju (Dept. of Electrical and Electronic Engineering, Yonsei University1, Image Sensor Team, Hanwha Thales)
Sohn, Kwanghoon (Dept. of Electrical and Electronic Engineering, Yonsei University1)
Publication Information
Journal of Korea Multimedia Society / v.19, no.5, 2016 , pp. 865-873 More about this Journal
Abstract
In recent years, Tracking-Learning-Detection(TLD) system has been widely used as a detection and tracking algorithm for vision sensors. While conventional algorithms are vulnerable to occlusion, and changes in illumination and appearances, TLD system is capable of robust tracking by conducting tracking, detection, and learning in real time. However, the detection and tracking algorithms of TLD system utilize rotation-variant features, and the margin of tracking error becomes greater when an object makes a full out-of-plane rotation. Thus, we propose a rotation-invariant TLD system(RI-TLD). we propose a simplified average orientation histogram and rotation matrix for a rotation inference algorithm. Experimental results with various tracking tests demonstrate the robustness and efficiency of the proposed system.
Keywords
Tracking-Learning-Detection; TLD; Rotation Invariant; Simplified Average Orientation Histogram;
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Times Cited By KSCI : 1  (Citation Analysis)
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