A Method for Enforcing Integrability in Shape from Shading Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rotation Invariant Neural Network-Based Face Detection
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Hierarchical Wavelet Networks for Facial Feature Localization
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Face Processing: Advanced Modeling and Methods
Face Processing: Advanced Modeling and Methods
Pose Angle Determination by Face, Eyes and Nose Localization
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Regression and Classification Approaches to Eye Localization in Face Images
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Multi-view face and eye detection using discriminant features
Computer Vision and Image Understanding
Extracting eyebrow contour and chin contour for face recognition
Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Efficient Multimodal 2D-3D Hybrid Approach to Automatic Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Deformable templates for face recognition
Journal of Cognitive Neuroscience
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This paper presents a new technique for three-dimensional face analysis aimed towards improving the robustness of face recognition. All of the 3D data used in the paper are obtained from a high-speed photometric stereo arrangement. First, a nose detection algorithm is presented, which is largely based on existing work, before a novel method for finding the nasion is described. Both of these methods rely solely on the 3D data. A new eye detection method is then described that uses a combination of 3D and 2D information with adaptive thresholding applied to the region of the image surrounding the eyes. The next main contribution of the paper is an analysis of the effects of makeup and facial hair on the success of the reconstruction and feature detection. We found that our method is very robust to such complications and can also handle spectacles and pose variation in many cases.