Title :
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
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;
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
DOI :
10.1109/CISP.2010.5647988
