Surface shape and curvature scales
Image and Vision Computing
COSMOS-A Representation Scheme for 3D Free-Form Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Overview of the Face Recognition Grand Challenge
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A 3D Facial Expression Database For Facial Behavior Research
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
3D Surface Matching and Recognition Using Conformal Geometry
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Description and retrieval of 3D face models using iso-geodesic stripes
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
High Resolution Tracking of Non-Rigid Motion of Densely Sampled 3D Data Using Harmonic Maps
International Journal of Computer Vision
Tracking vertex flow and model adaptation for three-dimensional spatiotemporal face analysis
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special issue on recent advances in biometrics
Bilinear Models for 3-D Face and Facial Expression Recognition
IEEE Transactions on Information Forensics and Security
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Research on 3D face models relies on extraction of feature points for segmentation, registration, or recognition. Robust feature point extraction from pure geometric surface data is still a challenging issue. In this project, we attempt to automatically extract feature points from 3D range face models without texture information. Human facial surface is overall convex in shape and a majority of the feature points are contained in concave regions within this generally convex structure. These "feature-rich" regions occupy a relatively small portion of the entire face surface area. We propose a novel approach that looks for features only in regions with a high density of concave points and ignores all convex regions. We apply an iso-geodesic stripe approach to limit the search region, and apply the shape-index integral projection to locate the features of interest. Finally, eight individual features (i.e., inner corners of eye, outer corners of eye, nose sides, and outer lip corners) are detected on 3D range models. The algorithm is evaluated on publicly available 3D databases and achieved over 90% accuracy on average.