This paper presents an approach to human motion tracking using multiple pre-trained activity models for propagation of particles in Annealed Particle Filtering. Hidden Markov models are trained on dimensionally reduced joint angle data to produce models of activity. Particles are divided between models for propagation by HMM synthesis, before converging on a solution during the annealing process. The approach facilitates multi-view tracking of unknown subjects performing multiple known activities with low particle numbers.
Published in
19th International Conference on Pattern Recognition (ICPR 2008)
19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6Pages
3125 - 3128 (4)Citation
DARBY, J., LI, B. and COSTEN, N., 2008. Behaviour based particle filtering for human articulated motion tracking. 19th International Conference on Pattern Recognition (ICPR 2008), Tampa, FL, 8th-11th December 2008, pp.3125 -3128Publisher
© IEEEVersion
AM (Accepted Manuscript)Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Publication date
2008Notes
This is the accepted manuscript version of the paper. © 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.ISBN
9781424421749;9781424421756ISSN
1051-4651Language
enLocation
Tampa, FL