Application of Time-varying Acceleration Coefficients PSO to Face Pose Estimation

DOI

10.2991/icismme-15.2015.12How to use a DOI?

Keywords

Face pose estimation; particle swarm optimization; time-varying acceleration coefficients; genetic algorithm; noise-free.

Abstract

This study focuses on the problem of human face pose estimation based on single image. Traditional methods for 2D-3D feature based pose estimation problem require two inputs, and they cannot work well due to lack of correspondences of input images. We transfer the problem into an optimization problem via six-point template, and solve the problem by time-varying acceleration coefficients particle swarm optimization (TVAC-PSO). Experiments on 40 different poses demonstrate that the TVAC-PSO is superior to either GA or PSO in terms of accuracy.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Yudong Zhang
AU  - Shuihua Wang
AU  - Genlin JI
PY  - 2015/07
DA  - 2015/07
TI  - Application of Time-varying Acceleration Coefficients PSO to Face Pose Estimation
BT  - Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy
PB  - Atlantis Press
SP  - 63
EP  - 68
SN  - 1951-6851
UR  - https://doi.org/10.2991/icismme-15.2015.12
DO  - 10.2991/icismme-15.2015.12
ID  - Zhang2015/07
ER  -