LAFTER: Lips and Face Real-Time Tracker
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Elliptical Head Tracking Using Intensity Gradients and Color Histograms
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
A unified approach to coding and interpreting face images
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Pose Estimation using 3D View-Based Eigenspaces
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
On the detection of feature points of 3D facial image and its application to 3D facial caricature
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
Surface Curvature as a Measure of Image Texture
IEEE Transactions on Pattern Analysis and Machine Intelligence
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This paper introduces an automated 3D face pose estimation method using the tetrahedral structure of a nose. This method is based on the feature points extracted from a face surface using curvature descriptors. A nose is the most protruding component in a 3D face image. A nose shape that is composed of the feature points such as a nasion, nose tip, nose base, and nose lobes, and is similar to a tetrahedron. Face pose can be estimated by fitting the tetrahedron to the coordinate axes. Each feature point can be localized by curvature descriptors. This method can be established using nasion, nose tip, and nose base. It can be applied to face tracking and face recognition.