Reliable and fast tracking of faces under varying pose

This paper presents a system that is able to track multiple faces under varying pose (tilted and rotated) reliably in real-time. The system consists of two interactive modules. The first module performs detection of face subject to rotations. The second does online learning based face tracking. A mechanism of switching between the two modules is embedded into the system to automatically decide the best strategy for reliable tracking. The mechanism enables smooth transit between the detection and tracking module when one of them gives no results or unreliable results. Results demonstrate that the system can make reliable real-time tracking of multiple faces in complex background under out-of-plane rotation, up to 90 degree tilting, fast nonlinear motion, partial occlusion, large scale changes, and camera motion

[1]  Harry Shum,et al.  Statistical Learning of Multi-view Face Detection , 2002, ECCV.

[2]  Paul A. Viola,et al.  Fast Multiview Face Detection , 2003 .

[3]  Stanley T. Birchfield,et al.  Elliptical head tracking using intensity gradients and color histograms , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[4]  Kentaro Toyama,et al.  Prolegomena for Robust Face Tracking , 1998 .

[5]  Paul A. Viola,et al.  Boosting Image Retrieval , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[6]  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).

[7]  Gang Hua,et al.  Tracking appearances with occlusions , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[8]  Alain Crouzil,et al.  Non-rigid object localization from color model using mean shift , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[9]  Dorin Comaniciu,et al.  Real-time tracking of non-rigid objects using mean shift , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[10]  Norbert Krüger,et al.  Face Recognition by Elastic Bunch Graph Matching , 1997, CAIP.

[11]  Raphaël Féraud,et al.  A fast and accurate face detector for indexation of face images , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[12]  Shaogang Gong,et al.  An investigation into face pose distributions , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.

[13]  Michael Isard,et al.  CONDENSATION—Conditional Density Propagation for Visual Tracking , 1998, International Journal of Computer Vision.

[14]  Dorin Comaniciu,et al.  Kernel-Based Object Tracking , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Qiang Ji,et al.  Multi-view face detection under complex scene based on combined SVMs , 2004, ICPR 2004.

[16]  Shihong Lao,et al.  Boosting nested cascade detector for multi-view face detection , 2004, ICPR 2004.

[17]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[18]  Paul A. Viola,et al.  Fast Multi-view Face Detection , 2003 .