NDLI: Kernel based articulated object tracking with scale adaptation and model update

Content Provider	IEEE Xplore Digital Library
Author	Anbang Yao Guijin Wang Xinggang Lin Hao Wang
Copyright Year	2008
Description	Author affiliation: Dept. of Electron. Eng., Tsinghua Univ., Beijing (Anbang Yao; Guijin Wang; Xinggang Lin)
Abstract	Kernel based object tracking (KBOT) is one of the most popular and effective techniques for tracking task. However the constancy of the target model and unsound scale adaptation method are two main limitations. In this paper, we present a kernel based approach incorporated with scale estimation and target model update for articulated object tracking task. After predicating the object center with scale fixed KBOT, we extend scale selection theory to estimate the local optimal object scale. Once the object scale has been estimated, a kernel density estimation based strategy is developed to update the target model. Experimental results show that our approach is superior to traditional KBOT in the following two aspects: 1) it is less affected by the object scale change; 2) it is less prone to appearance variation.
Starting Page	945
Ending Page	948
File Size	229726
Page Count	4
File Format	PDF
ISBN	9781424414833
ISSN	15206149
DOI	10.1109/ICASSP.2008.4517767
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-03-31
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kernel Adaptation model Target tracking Bandwidth Video compression Concurrent computing Convergence Interleaved codes Robustness Extraterrestrial measurements Scale space Articulated object Kernel based object tracking Kernel density estimation
Content Type	Text
Resource Type	Article

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