Presentation 2007-10-26
Sequential Monte Carlo Object Tracking Method with a Histogram-based Observation Model
Yuichi MIYAJIMA, Atsushi MATSUI, Yohei NAKADA, Takashi MATSUMOTO,
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Abstract(in English) SMC(Sequential Monte Carlo) method can deal with nonlinear and multimodal probability distributions by drawing and updating i.i.d. samples sequentially. And computational cost of the algorithm would strongly depend on the total number of samples, if we opt a highly complicated likelihood function which describes relationship between given data and parameters. In this paper, we propose a new likelihood function for object tracking problem, based on the histogram given target sample image. Some experimental results show that our new model successfully boost its processing speed up to 37 times faster than that of baseline model, without sacrificing any tracking accuracy.
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Keyword(in English) object tracking / sequential Monte Carlo / color histogram / computational cost
Paper # PRMU2007-105
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Committee PRMU
Conference Date 2007/10/18(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Sequential Monte Carlo Object Tracking Method with a Histogram-based Observation Model
Sub Title (in English)
Keyword(1) object tracking
Keyword(2) sequential Monte Carlo
Keyword(3) color histogram
Keyword(4) computational cost
1st Author's Name Yuichi MIYAJIMA
1st Author's Affiliation Faculty of Science and Engineering, Waseda University()
2nd Author's Name Atsushi MATSUI
2nd Author's Affiliation Faculty of Science and Engineering, Waseda University:Science & Technical Research Laboratories, Japan Broadcasting Corporation (NHK)
3rd Author's Name Yohei NAKADA
3rd Author's Affiliation Faculty of Science and Engineering, Waseda University
4th Author's Name Takashi MATSUMOTO
4th Author's Affiliation Faculty of Science and Engineering, Waseda University
Date 2007-10-26
Paper # PRMU2007-105
Volume (vol) vol.107
Number (no) 281
Page pp.pp.-
#Pages 6
Date of Issue