@inproceedings{48d3d0b0e1fa45faa132cb6e6228f124,
title = "Application of TS-PSO to face pose estimation",
abstract = "This study centers around the problem of single image based human face pose estimation. We transfer the problem into an optimization problem via six-point template, and solve the problem by a combination of Tabu search and particle swarm optimization. The combined method is termed TS-PSO, which makes full use of the exploration ability of PSO and the exploitation ability of TS and offsets the weaknesses of each other. Experiments on Error! Reference source not found. different poses demonstrate that the TS-PSO is superior to either GA or PSO in terms of estimation accuracy.",
keywords = "Face pose estimation, Genetic algorithm, Particle swarm optimization, Tabu search",
author = "Shuihua Wang and Yudong Zhang and Genlin Ji",
note = "Publisher Copyright: {\textcopyright} 2015 Taylor & Francis Group, London.; Proceedings of the Asia-Pacific Conference on Computer Science and Applications, CSAC 2014 ; Conference date: 27-12-2014 Through 28-12-2014",
year = "2015",
doi = "10.1201/b18508-22",
language = "English",
isbn = "9781138028111",
series = "Computer Science and Applications - Proceedings of the Asia-Pacific Conference on Computer Science and Applications, CSAC 2014",
publisher = "CRC Press/Balkema",
pages = "117--122",
editor = "Ally Hu",
booktitle = "Computer Science and Applications - Proceedings of the Asia-Pacific Conference on Computer Science and Applications, CSAC 2014",
}