Paper
19 August 2010 Study on vision object tracking based on adaptive object segmentation
Hui-Juan Hao, Ji-Yong Xu, Guang-Qi Liu
Author Affiliations +
Proceedings Volume 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering; 782014 (2010) https://doi.org/10.1117/12.866384
Event: International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 2010, Xi'an, China
Abstract
In order to solve the object tracking under occlusion, the adaptively tracking algorithm is proposed based on color features. The object is adaptively divided using fuzzy k-means clustering algorithm, and the sub-regions are weighted with monotone decreasing kernel function. The object model is updated through mean value of sub- regions' colors, so the calculation is simple. During the object tracking, the method of integral matching is used; combining with the adaptive Kalman filter, the object tracking under occlusion is resolved effectively. The experiments show that the new algorithm can track the object exactly.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hui-Juan Hao, Ji-Yong Xu, and Guang-Qi Liu "Study on vision object tracking based on adaptive object segmentation", Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 782014 (19 August 2010); https://doi.org/10.1117/12.866384
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KEYWORDS
Detection and tracking algorithms

Filtering (signal processing)

Fuzzy logic

RGB color model

Electronic filtering

Image processing algorithms and systems

Motion models

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