Tracking facial features using Gabor wavelet networks

The work presents a method for automatic facial feature tracking in video sequences. In this method, a discrete face template is represented as a linear combination of continuous 2D odd-Gabor wavelet functions. The weights and 2D parameters (position, scale and orientation) of each wavelet are determined optimally so that the maximum amount of image information is preserved for a given number of wavelets. We have used this representation to achieve effective facial feature tracking that is robust to homogeneous illumination changes and affine deformations of the face image. Moreover, the tracking approach considers the overall geometry of the face, being robust to facial feature deformations such as eye blinking and smiling. The number of wavelets in the representation may be chosen with respect to the available computational resources, even allowing real time processing.

[1]  William H. Press,et al.  Numerical recipes , 1990 .

[2]  Roberto Marcondes Cesar Junior,et al.  Detection and Tracking of Facial Features in Video Sequences , 2000, MICAI.

[3]  Alexander H. Waibel,et al.  Skin-Color Modeling and Adaptation , 1998, ACCV.

[4]  Rainer Stiefelhagen,et al.  Gaze tracking for multimodal human-computer interaction , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[5]  J. Daugman.  Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[6]  Christoph von der Malsburg,et al.  Tracking and learning graphs and pose on image sequences of faces , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.

[7]  J. E. Glynn,et al.  Numerical Recipes: The Art of Scientific Computing , 1989 .

[8]  Ingrid Daubechies,et al.  The wavelet transform, time-frequency localization and signal analysis , 1990, IEEE Trans. Inf. Theory.

[9]  G. Sommer,et al.  Affine real-time face tracking using a wavelet network , 1999, Proceedings International Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems. In Conjunction with ICCV'99 (Cat. No.PR00378).

[10]  Harold H. Szu,et al.  Neural network adaptive wavelets for signal representation and classification , 1992 .

[11]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Kiyoharu Aizawa,et al.  Detection and tracking of facial features , 1995, Other Conferences.

[13]  Alexander H. Waibel,et al.  A real-time face tracker , 1996, Proceedings Third IEEE Workshop on Applications of Computer Vision. WACV'96.

[14]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1992, Math. Control. Signals Syst..