期刊名称:International Journal of Advanced Robotic Systems
印刷版ISSN:1729-8806
电子版ISSN:1729-8814
出版年度:2016
卷号:13
期号:5
DOI:10.1177/1729881416662793
语种:English
出版社:SAGE Publications
摘要:For robot systems, robust facial landmark detection is the first and critical step for face-based human identification and facial expression recognition. In recent years, the cascaded-regression-based method has achieved excellent performance in facial landmark detection. Nevertheless, it still has certain weakness, such as high sensitivity to the initialization. To address this problem, regression based on multiple initializations is established in a unified model; face shapes are then estimated independently according to these initializations. With a ranking strategy, the best estimate is selected as the final output. Moreover, a face shape model based on restricted Boltzmann machines is built as a constraint to improve the robustness of ranking. Experiments on three challenging datasets demonstrate the effectiveness of the proposed facial landmark detection method against state-of-the-art methods.