NDLI: An improved unscented particle filter for visual hand tracking

Content Provider	IEEE Xplore Digital Library
Author	Hanxuan Yang Zhan Song Runen Chen
Copyright Year	2010
Description	Author affiliation: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China (Hanxuan Yang; Zhan Song) \|\| Department of Electronic & Information Engineering South China Agricultural University Guangzhou, China (Runen Chen)
Abstract	Hand tracking is an active research topic in Human Computer Interaction (HCI). In this paper, we present an improved Unscented Particle Filter (UPF) combined with the incremental Principle Component Analysis (IPCA) method for the visual hand tracking. The Singular Value Decomposition (SVD) approach is introduced to compute the sigma points and then to obtain the proposal distribution within the Unscented Kalman Filter (UKF) framework. The experiments are conducted on an indoor scene with complex background and the results are also compared with some traditional tracking methods to show its strong robustness and higher tracking precision.
Starting Page	427
Ending Page	431
File Size	346155
Page Count	5
File Format	PDF
ISBN	9781424465132
e-ISBN	9781424465163
DOI	10.1109/CISP.2010.5647988
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	unscented particle filter Visualization Computer vision human hand tracking Tracking Computational modeling Adaptation model incremental learning Particle filters Robustness singular value decomposition
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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