Recognition of Human Faces: From Biological to Artificial Vision

Face recognition is among the most challenging techniques for personal identity verification. Even though it is so natural for humans, there are still many hidden mechanisms which are still to be discovered. According to the most recent neurophysiological studies, the use of dynamic information is extremely important for humans in visual perception of biological forms and motion. Moreover, motion processing is also involved in the selection of the most informative areas of the face and consequently directing the attention. This paper provides an overview and some new insights on the use of dynamic visual information for face recognition, both for exploiting the temporal information and to define the most relevant areas to be analyzed on the face. In this context, both physical and behavioral features emerge in the face representation.

[1]  Biing-Hwang Juang,et al.  HMM clustering for connected word recognition , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[2]  Uday B. Desai,et al.  Face recognition using a DCT-HMM approach , 1998, Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201).

[3]  Giorgio Bonmassar,et al.  Space-variant active vision: Definition, overview and examples , 1995, Neural Networks.

[4]  Peter J. Burt,et al.  `Smart Sensing' in machine vision , 1988 .

[5]  Rosalind W. Picard.  Building HAL: computers that sense, recognize, and respond to human emotion , 2001, IS&T/SPIE Electronic Imaging.

[6]  Michel Vidal-Naquet,et al.  Visual features of intermediate complexity and their use in classification , 2002, Nature Neuroscience.

[7]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[8]  Johan Stephen Simeon Ballot.  Face recognition using Hidden Markov Models , 2005 .

[9]  Enrico Grosso,et al.  Probabilistic face authentication using hidden Markov models , 2005, SPIE Defense + Commercial Sensing.

[10]  Ze-Nian Li,et al.  Reciprocal-Wedge Transform for Space-Variant Sensing , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  J. Fagan,et al.  Infants' recognition memory for faces. , 1972, Journal of experimental child psychology.

[12]  Cen Li,et al.  A bayesian approach to temporal data clustering using the hidden markov model methodology , 2000 .

[13]  Manuele Bicego,et al.  A Hidden Markov Model-Based Approach to Sequential Data Clustering , 2002, SSPR/SPR.

[14]  Padhraic Smyth,et al.  Clustering Sequences with Hidden Markov Models , 1996, NIPS.

[15]  David J. Kriegman,et al.  Video-based face recognition using probabilistic appearance manifolds , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[16]  Jongsun Kim,et al.  Effective representation using ICA for face recognition robust to local distortion and partial occlusion , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Albert Ali Salah,et al.  A Selective Attention-Based Method for Visual Pattern Recognition with Application to Handwritten Digit Recognition and Face Recognition , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Tony Lindeberg,et al.  Detecting salient blob-like image structures and their scales with a scale-space primal sketch: A method for focus-of-attention , 1993, International Journal of Computer Vision.

[19]  Zoran Biuk,et al.  Face recognition from multi-pose image sequence , 2001, ISPA 2001. Proceedings of the 2nd International Symposium on Image and Signal Processing and Analysis. In conjunction with 23rd International Conference on Information Technology Interfaces (IEEE Cat..

[20]  Thomas D. Albright,et al.  How Do Monkeys Look at Faces? , 1997, Journal of Cognitive Neuroscience.

[21]  Gautam Biswas,et al.  A Bayesian Approach to Temporal Data Clustering using Hidden Markov Models , 2000, ICML.

[22]  Norbert Krüger,et al.  Face recognition by elastic bunch graph matching , 1997, Proceedings of International Conference on Image Processing.

[23]  A. O'Toole,et al.  Recognizing moving faces: a psychological and neural synthesis , 2002, Trends in Cognitive Sciences.

[24]  Gabriela Csurka,et al.  Visual categorization with bags of keypoints , 2002, eccv 2004.

[25]  Pietro Perona,et al.  Object class recognition by unsupervised scale-invariant learning , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[26]  Anil K. Jain,et al.  Algorithms for Clustering Data , 1988 .

[27]  Garrison W. Cottrell,et al.  EMPATH: Face, Emotion, and Gender Recognition Using Holons , 1990, NIPS.

[28]  C. Darwin.  The Expression of the Emotions in Man and Animals , .

[29]  C. C. Goren,et al.  Visual following and pattern discrimination of face-like stimuli by newborn infants. , 1975, Pediatrics.

[30]  Dan Roth,et al.  Learning a Sparse Representation for Object Detection , 2002, ECCV.

[31]  A. L. Yarbus,et al.  Eye Movements and Vision , 1967, Springer US.

[32]  Penio S. Penev,et al.  Local feature analysis: A general statistical theory for object representation , 1996 .

[33]  Dana H. Ballard,et al.  Animate Vision , 1991, Artif. Intell..

[34]  A. Hendrickson,et al.  Human photoreceptor topography , 1990, The Journal of comparative neurology.

[35]  Yehezkel Yeshurun,et al.  Shape Description with a Space-Variant Sensor: Algorithms for Scan-Path, Fusion, and Convergence Over Multiple Scans , 2015, IEEE Trans. Pattern Anal. Mach. Intell..

[36]  S Ullman,et al.  Shifts in selective visual attention: towards the underlying neural circuitry. , 1985, Human neurobiology.

[37]  Brendan J. Frey,et al.  Epitomic analysis of appearance and shape , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[38]  P. Sinha,et al.  Functional neuroanatomy of biological motion perception in humans , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[39]  Enrico Grosso,et al.  Person Authentication from Video of Faces: A Behavioral and Physiological Approach Using Pseudo Hierarchical Hidden Markov Models , 2006, ICB.

[40]  Ze-Nian Li,et al.  The reciprocal-wedge transform for space-invariant sensing , 1993, 1993 (4th) International Conference on Computer Vision.

[41]  Rosalind W. Picard.  Toward computers that recognize and respond to user emotion , 2000, IBM Syst. J..

[42]  J. Haxby,et al.  The distributed human neural system for face perception , 2000, Trends in Cognitive Sciences.

[43]  A. Johnston,et al.  The Role of Movement in Face Recognition , 1997 .

[44]  Richard D. Juday,et al.  A Programmable Video Image Remapper , 1988, Defense, Security, and Sensing.

[45]  C. Nelson,et al.  Recognition of the mother's face by six-month-old infants: a neurobehavioral study. , 1997, Child development.

[46]  Massimo Tistarelli,et al.  Active/space-variant object recognition , 1995, Image Vis. Comput..

[47]  Rama Chellappa,et al.  Probabilistic recognition of human faces from video , 2002, Proceedings. International Conference on Image Processing.

[48]  Vicki Bruce,et al.  Face Recognition: From Theory to Applications , 1999 .

[49]  Manuele Bicego,et al.  Using hidden Markov models and wavelets for face recognition , 2003, 12th International Conference on Image Analysis and Processing, 2003.Proceedings..

[50]  Cordelia Schmid,et al.  Selection of scale-invariant parts for object class recognition , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[51]  Norbert Krüger,et al.  Face Recognition and Gender determination , 1995 .

[52]  Giulio Sandini,et al.  Retina-Like Sensors: Motivations, Technology and Applications , 2003 .

[53]  Tsuhan Chen,et al.  Video-based face recognition using adaptive hidden Markov models , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[54]  Ken-ichi Maeda,et al.  Face recognition using temporal image sequence , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

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

[56]  E. L. Schwartz,et al.  Spatial mapping in the primate sensory projection: Analytic structure and relevance to perception , 1977, Biological Cybernetics.

[57]  Monson H. Hayes,et al.  Hidden Markov models for face recognition , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[58]  Enrico Grosso,et al.  On Finding Differences Between Faces , 2005, AVBPA.

[59]  Yoram Singer,et al.  The Hierarchical Hidden Markov Model: Analysis and Applications , 1998, Machine Learning.

[60]  Enrico Grosso,et al.  Active vision-based face authentication , 2000, Image Vis. Comput..

[61]  G. Schwarz.  Estimating the Dimension of a Model , 1978 .

[62]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[63]  Stan Z. Li,et al.  Learning spatially localized, parts-based representation , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[64]  John K. Tsotsos,et al.  Modeling Visual Attention via Selective Tuning , 1995, Artif. Intell..

[65]  T. Bower,et al.  Newborns Form “Prototypes” in Less Than 1 Minute , 1993 .

[66]  B. Braathen,et al.  First steps towards automatic recognition of spontaneous facial action units , 2001, PUI '01.

[67]  Matti Pietikäinen,et al.  Electronic Letters on Computer Vision and Image Analysis 5(1):1-13, 2005 An Experimental Investigation about the Integration of Facial Dynamics in Video-Based Face Recognition , 2004 .

[68]  Yiannis Aloimonos,et al.  Purposive, qualitative, active vision , 1992, CVGIP Image Underst..

[69]  Trevor Darrell,et al.  Face Recognition from Long-Term Observations , 2002, ECCV.

[70]  Daniel González-Jiménez,et al.  Discriminative Face Recognition Through Gabor Responses and Sketch Distortion , 2005, IbPRIA.

[71]  M. Haith,et al.  Eye contact and face scanning in early infancy. , 1978, Science.

[72]  Enrico Grosso,et al.  Log-polar Stereo for Anthropomorphic Robots , 2000, ECCV.