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Proceedings Paper

Object tracking with revised SMOG model
Author(s): Huan Wang; Mingwu Ren; Jingyu Yang
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Paper Abstract

Spatial color Mixture Of Gaussians model (SMOG model) based similarity measure is superior to the popular color histogram based one since it considers not only the colors in a region, but also the spatial layout of these colors. However, two drawbacks of SMOG are still obvious, firstly, in the initialization of SMOG, some background pixels are inevitably introduced and clustered as an object mode for tracking, this often degenerates the tracking performance. Secondly, the weight of each Gaussian mode is restricted by the probability of the pixels belong to it, so a low probability Gaussian mode always contribute a little in similarity measure even it has a high discrimination for discriminating the object. A revised SMOG model is proposed to efficiently cope with these two problems by sufficiently considering the object local background. Experiment results on synthetic and real image sequences verified the validity of the revised model.

Paper Details

Date Published: 15 November 2007
PDF: 8 pages
Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67880Y (15 November 2007); doi: 10.1117/12.748682
Show Author Affiliations
Huan Wang, Nanjing Univ. of Science and Technology (China)
Mingwu Ren, Nanjing Univ. of Science and Technology (China)
Jingyu Yang, Nanjing Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 6788:
MIPPR 2007: Pattern Recognition and Computer Vision
S. J. Maybank; Mingyue Ding; F. Wahl; Yaoting Zhu, Editor(s)

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