An improved unscented particle filter for visual hand tracking

Author

Yang, Hanxuan ; Song, Zhan ; Chen, Runen

Author_Institution

Shenzhen Institutes of Adv. Technol., Chinese Acad. of Sci., Shenzhen, China

Volume

1

fYear

2010

fDate

16-18 Oct. 2010

Firstpage

427

Lastpage

431

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.

Keywords

Kalman filters; particle filtering (numerical methods); target tracking; human computer interaction; indoor scene; principle component analysis; singular value decomposition; unscented Kalman filter; unscented particle filter; visual hand tracking; Adaptation model; Computational modeling; Computer vision; Particle filters; Robustness; Tracking; Visualization; human hand tracking; incremental learning; singular value decomposition; unscented particle filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing (CISP), 2010 3rd International Congress on

Conference_Location

Yantai

Print_ISBN

978-1-4244-6513-2

Type

conf

DOI

10.1109/CISP.2010.5647988

Filename

5647988