A Swarm Intelligence Based Searching Strategy for Articulated 3D Human Body Tracking
Abstract
This paper proposes an annealed particle swarm optimization based particle filter algorithm for articulated 3D human body tracking. In our algorithm, a sampling covariance and an annealing factor are incorporated into the velocity updating equation of particle swarm optimization (PSO). The sampling covariance and the annealing factor are initiated with appropriate values at the beginning of the PSO iteration, and `annealing' is carried out at reasonable steps. Experiments with multi-camera walking sequences from the Brown dataset show that: 1) the proposed tracker can effectively alleviate the problem of inconsistency between the image likelihood and the true model; 2) the tracker is also robust to noise and body self-occlusion.
Cite
Text
Zhang et al. "A Swarm Intelligence Based Searching Strategy for Articulated 3D Human Body Tracking." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2010. doi:10.1109/CVPRW.2010.5543804Markdown
[Zhang et al. "A Swarm Intelligence Based Searching Strategy for Articulated 3D Human Body Tracking." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2010.](https://mlanthology.org/cvprw/2010/zhang2010cvprw-swarm/) doi:10.1109/CVPRW.2010.5543804BibTeX
@inproceedings{zhang2010cvprw-swarm,
title = {{A Swarm Intelligence Based Searching Strategy for Articulated 3D Human Body Tracking}},
author = {Zhang, Xiaoqin and Hu, Weiming and Wang, Xiangyang and Kong, Yu and Xie, Nianhua and Wang, Hanzi and Ling, Haibin and Maybank, Stephen J.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2010},
pages = {45-50},
doi = {10.1109/CVPRW.2010.5543804},
url = {https://mlanthology.org/cvprw/2010/zhang2010cvprw-swarm/}
}