Preprocessing of Face Images: Detection of Features and Pose Normalization

The reliability, speed, and complexity of virtually any face recognition system are substantially improved if the location and the scale of the faces are known. We propose a method for automatic and robust detection of the eyes and mouth using the context freegeneralized symmetry transformand knowledge of faces. The features are extracted from the image of the intensities gradients and are then used to normalize the face images. We show that a normalization procedure based on affine transformations whose anchor points are the locations of the eyes and mouth substantially increases the effectiveness of general purpose classification techniques in face recognition.Other normalization procedures for avoiding the effect of background and varying light conditions are proved to be instrumental as well.

[1]  F. Galton.  Composite Portraits, Made by Combining Those of Many Different Persons Into a Single Resultant Figure. , 1879 .

[2]  A. L. I︠A︡rbus.  Eye Movements and Vision , 1967 .

[3]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[4]  Takeo Kanade,et al.  Picture Processing System by Computer Complex and Recognition of Human Faces , 1974 .

[5]  Azriel Rosenfeld,et al.  Scene Labeling by Relaxation Operations , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[6]  H. Ellis,et al.  Face recognition accuracy as a function of mode of representation. , 1978 .

[7]  Robert J. Baron,et al.  Mechanisms of Human Facial Recognition , 1981, Int. J. Man Mach. Stud..

[8]  Norman I. Badler,et al.  Animating facial expressions , 1981, SIGGRAPH '81.

[9]  Takeo Kanade,et al.  Mapping Image Properties into Shape Constraints: Skewed Symmetry, Affine-Transformable Patterns, and the Shape-from-Texture Paradigm , 1983 .

[10]  T. J. Stonham,et al.  Practical Face Recognition and Verification with Wisard , 1986 .

[11]  I. Fraser,et al.  Reaction Time Measures of Feature Saliency in a Perceptual Integration Task , 1986 .

[12]  Alice J. O'Toole,et al.  Recognition memory transfer between spatial-frequency analyzed faces , 1986 .

[13]  Nigel D. Haig,et al.  Investigating Face Recognition with an Image Processing Computer , 1986 .

[14]  Ian Craw,et al.  Automatic extraction of face-features , 1987, Pattern Recognit. Lett..

[15]  Peter J. Burt,et al.  Smart sensing within a pyramid vision machine , 1988, Proc. IEEE.

[16]  Vicki Bruce,et al.  COMPUTER RECOGNITION OF FACES , 1989 .

[17]  Demetri Terzopoulos,et al.  Physically-based facial modelling, analysis, and animation , 1990, Comput. Animat. Virtual Worlds.

[18]  Lawrence Sirovich,et al.  Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Yehezkel Yeshurun,et al.  Detection of interest points using symmetry , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[20]  Venu Govindaraju,et al.  A computational model for face location , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[21]  Demetri Terzopoulos,et al.  Modelling and animating faces using scanned data , 1991, Comput. Animat. Virtual Worlds.

[22]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[23]  Ashok Samal,et al.  Automatic recognition and analysis of human faces and facial expressions: a survey , 1992, Pattern Recognit..

[24]  Yehezkel Yeshurun,et al.  Robust detection of facial features by generalized symmetry , 1992, [1992] Proceedings. 11th IAPR International Conference on Pattern Recognition.

[25]  Shimon Edelman,et al.  Learning to Recognize Faces from Examples , 1992, ECCV.

[26]  Rama Chellappa,et al.  A feature based approach to face recognition , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[27]  Roberto Brunelli,et al.  Face Recognition: Features Versus Templates , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[28]  M. Farah,et al.  Parts and Wholes in Face Recognition , 1993, The Quarterly journal of experimental psychology. A, Human experimental psychology.

[29]  Yehezkel Yeshurun,et al.  Normalization of face images using few anchors , 1994, Proceedings of 12th International Conference on Pattern Recognition.

[30]  Michael C. Burl,et al.  Finding faces in cluttered scenes using random labeled graph matching , 1995, Proceedings of IEEE International Conference on Computer Vision.

[31]  D. Reisfeld,et al.  Extraction of Facial Features for Recognitionusing Neural , 1995 .

[32]  Alex Pentland,et al.  Facial expression recognition using a dynamic model and motion energy , 1995, Proceedings of IEEE International Conference on Computer Vision.

[33]  Timothy F. Cootes,et al.  A unified approach to coding and interpreting face images , 1995, Proceedings of IEEE International Conference on Computer Vision.

[34]  Alex Pentland,et al.  Probabilistic visual learning for object detection , 1995, Proceedings of IEEE International Conference on Computer Vision.

[35]  D. Reisfeld,et al.  Face recognition using a hybrid supervised/unsupervised neural network , 1996, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

[36]  Daniel Reisfeld,et al.  The constrained phase congruency feature detector: simultaneous localization, classification and scale determination , 1996, Pattern Recognit. Lett..

[37]  Richard W. Longman,et al.  Liapunov Stability of Force-Controlled Grasps with a Multi-Fingered Hand , 1996, Int. J. Robotics Res..

[38]  Tomaso A. Poggio,et al.  Example-Based Learning for View-Based Human Face Detection , 1998, IEEE Trans. Pattern Anal. Mach. Intell..