Estimating face pose by facial asymmetry and geometry

A robust pose estimation approach is proposed by combining facial appearance asymmetry and 3D geometry in a coarse-to-fine framework. The rough face pose is first estimated by analyzing the asymmetry of the distribution of the facial component detection confidences on an image, which actually implies an intrinsic relation between the face pose and the facial appearance. Then, this rough face pose, as well as error bandwidth, is utilized into a 3D-to-2D geometrical model matching to refine the pose estimation. The proposed approach is able to track a face with fast motion in front of cluttered background and recover its pose robustly and accurately in real- time. Experiment results are provided to demonstrate its efficiency and accuracy.

[1]  Tao Daniel Alter.  3-D Pose from 3 Points Using Weak-Perspective , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Ralph Gross,et al.  Quo vadis Face Recognition , 2001 .

[3]  Bernhard Schölkopf,et al.  Kernel machine based learning for multi-view face detection and pose estimation , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[4]  Yanxi Liu,et al.  Facial Asymmetry: A New Biometric , 2001 .

[5]  Yanxi Liu,et al.  Facial asymmetry quantification for expression invariant human identification , 2003, Comput. Vis. Image Underst..

[6]  Harry Shum,et al.  Face alignment using texture-constrained active shape models , 2003, Image Vis. Comput..

[7]  P. Jonathon Phillips,et al.  Empirical Evaluation Methods in Computer Vision , 2002 .

[8]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.

[9]  Gregory D. Hager,et al.  Efficient Region Tracking With Parametric Models of Geometry and Illumination , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Hong Yan,et al.  An Analytic-to-Holistic Approach for Face Recognition Based on a Single Frontal View , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Paul A. Viola,et al.  Robust Real-time Object Detection , 2001 .

[12]  P J. Phillips,et al.  Face Recognition Vendor Test 2000: Evaluation Report , 2001 .

[13]  Sami Romdhani,et al.  Efficient, robust and accurate fitting of a 3D morphable model , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[14]  Alfred M. Bruckstein,et al.  Uniqueness of 3D Pose Under Weak Perspective: A Geometrical Proof , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Zicheng Liu,et al.  Robust head motion computation by taking advantage of physical properties , 2000, Proceedings Workshop on Human Motion.

[16]  Yi Zhou,et al.  Bayesian tangent shape model: estimating shape and pose parameters via Bayesian inference , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[17]  Ying Wu,et al.  Wide-range, person- and illumination-insensitive head orientation estimation , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[18]  P. Jonathon Phillips,et al.  Face recognition vendor test 2002 , 2003, 2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443).

[19]  Shaogang Gong,et al.  Support vector regression and classification based multi-view face detection and recognition , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[20]  Xinhua Zhuang,et al.  Optic Flow Field Segmentation and Motion Estimation Using a Robust Genetic Partitioning Algorithm , 1995, IEEE Trans. Pattern Anal. Mach. Intell..