Articulate hand motion capturing based on a Monte Carlo Nelder-Mead simplex tracker

John Lin*, Ying Wu, Thomas S. Huang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

This paper presents an algorithm for tracking the articulate hand motion in monocular video sequences. The task is challenging due to the high degrees of freedom involved in the hand motion. The complexity can be reduced by considering the natural motion constraints. To take advantage of the constraints, we propose to use a nonparametric representation of the feasible configuration space and employ a Monte Carlo Nelder-Mead simplex search algorithm. The tracker combines the strengths of both sequential Monte Carlo and direct search algorithms. First, its multiple hypotheses nature increases the chance of the simplex method to identify the global maximum. Second, the direct search algorithm produces a set of more representative particles. Experiment results show that this hybrid approach is robust for tracking the hand motion.

Original languageEnglish (US)
Title of host publicationProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
EditorsJ. Kittler, M. Petrou, M. Nixon
Pages975-978
Number of pages4
DOIs
StatePublished - Dec 20 2004
EventProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
Duration: Aug 23 2004Aug 26 2004

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume4
ISSN (Print)1051-4651

Other

OtherProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
CountryUnited Kingdom
CityCambridge
Period8/23/048/26/04

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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  • Cite this

    Lin, J., Wu, Y., & Huang, T. S. (2004). Articulate hand motion capturing based on a Monte Carlo Nelder-Mead simplex tracker. In J. Kittler, M. Petrou, & M. Nixon (Eds.), Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 (pp. 975-978). (Proceedings - International Conference on Pattern Recognition; Vol. 4). https://doi.org/10.1109/ICPR.2004.1333936