Application of Time-varying Acceleration Coefficients PSO to Face Pose Estimation
Yudong Zhang, Shuihua Wang, Genlin JI
Available Online July 2015.
- https://doi.org/10.2991/icismme-15.2015.12How to use a DOI?
- Face pose estimation; particle swarm optimization; time-varying acceleration coefficients; genetic algorithm; noise-free.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 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 - https://doi.org/10.2991/icismme-15.2015.12 ID - Zhang2015/07 ER -