3D facial landmark localization under pose and expression variations
LIANG Yan
ZHANG Yun
Abstract：Landmark localization on 3D facial scans is important for face recognition, tracking, modeling, expression analysis, and so on. However, landmark localization in the presence of large pose and expression variations is still a great challenge. In this paper, a method for 3D facial landmark localization is presented. The method is insensitive to pose and expression. Candidate landmarks are detected using HK curvature analysis. According to the priori knowledge on fa-cial shape, a facial geometrical structure-based classification strategy is proposed to subdivide the candidate landmarks. Landmark localization is obtained by matching candidate landmarks with a facial landmark model (FLM). The landmark localization accuracy of our method is first experimented on the CASIA dataset. Then, our method is compared with the state-of-the-art methods on the UND/FRGC v2.0 dataset. Experimental results confirm that our method achieves high accuracy and robustness both to large pose and expression variations.
Keywords：facial landmark localizationHK curvature analysisfacial landmark modelclassification strategymesh segmentation
Publication Date：2017-01-01
Pages：9( 820-828 )