Quasi Monte Carlo partitioned filtering for Visual Human Motion Capture

Author

Mathias, F. ; Patrick, Dave ; Frederic, L.

Author_Institution

LAAS, CNRS, Toulouse, France

fYear

2009

fDate

7-10 Nov. 2009

Firstpage

2553

Lastpage

2556

Abstract

Visual Human Motion Capture (HMC) is a motivating challenge in the Computer Vision community as it enables lots of applications. Many methods have been proposed among which Particle Filters (PF) meet a great success. In this paper, we propose a new algorithm, mixing advantages of the PARTITIONED scheme and quasi random methods. We use a trinocular visual system to propose a comparative study of this particle filter against four other classical ones with respect to a ground truth provided by a commercial HMC system.

Keywords

Monte Carlo methods; computer vision; image motion analysis; particle filtering (numerical methods); random processes; computer vision community; partitioned scheme method; quasi Monte Carlo partitioned filtering; quasi random methods; visual human motion capture; Filtering; Humans; Indium phosphide; Monte Carlo methods; Motion estimation; Particle filters; Particle tracking; State estimation; State-space methods; Uninterruptible power systems; Motion capture; particle filters; quasi random sampling; trinocular system;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing (ICIP), 2009 16th IEEE International Conference on

Conference_Location

Cairo

ISSN

1522-4880

Print_ISBN

978-1-4244-5653-6

Electronic_ISBN

1522-4880

Type

conf

DOI

10.1109/ICIP.2009.5414003

Filename

5414003