CONNECTIONIST APPROACHES TO VISUALLY-BASED FACIAL FEATURE EXTRACTION

We examine here some properties of a connectionist autoassociative matrix for storing, in a parallel and distributed fashion, face stimuli that are coded as simple patterns of spatially varying light intensities. First, we find that the opposition of positive and negative point contributions for nearly all the eigenvectors forms head/hair shapes, often containing the positions and shapes of eyes. Second, the opposition of positive and negative points that contribute strongly to the determination of the first eigenvector appear to separate male and female head/hair shapes. We find also that pixel positions that contribute strongly to the eigenvectors generally form spatially contiguous groups in the face pattern, often form face/head shapes, and occasionally consist of points that form a hairstyle. The results are discussed in terms of previous results indicating the salience of these ’features’ for discrimination and identification, and in terms of Bruce & Young’s (1986) visually-derived semantic

[1]  J. Hochberg,et al.  Recognition memory for photographs of faces. , 1971, The American journal of psychology.

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

[3]  G. Bower,et al.  Depth of processing pictures of faces and recognition memory , 1974 .

[4]  H. Ellis Recognizing faces. , 1975, British journal of psychology.

[5]  Robert E. Shaw,et al.  Perception of relative and absolute age in facial photographs , 1975 .

[6]  J. B. Pittenger,et al.  Aging faces as viscal-elastic events: implications for a theory of nonrigid shape perception. , 1975, Journal of experimental psychology. Human perception and performance.

[7]  Stephen A. Ritz,et al.  Distinctive features, categorical perception, and probability learning: some applications of a neural model , 1977 .

[8]  Teuvo Kohonen,et al.  Associative memory. A system-theoretical approach , 1977 .

[9]  V. Bruce Searching for Politicians: An Information-Processing Approach to Face Recognition , 1979 .

[10]  H D Ellis,et al.  Similarity effects in face recognition. , 1979, The American journal of psychology.

[11]  J. Shepherd Studies of cue saliency , 1981 .

[12]  A. Young,et al.  The human face , 1982 .

[13]  A. W. Ellis Normality and pathology in cognitive functions , 1982 .

[14]  J. Sergent The cerebral balance of power: confrontation or cooperation? , 1982, Journal of experimental psychology. Human perception and performance.

[15]  R L Klatzky,et al.  Semantic interpretation effects on memory for faces , 1982, Memory & cognition.

[16]  Igor Aleksander,et al.  Emergent intelligent properties of progressively structured pattern recognition nets , 1983, Pattern Recognit. Lett..

[17]  G. Rhodes Lateralized processes in face recognition. , 1985, British journal of psychology.

[18]  A. Young,et al.  Understanding face recognition. , 1986, British journal of psychology.

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

[20]  Hervé Abdi Faces, Prototypes, and Additive Tree Representations , 1986 .

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

[22]  Do we really need a ‘contingency model’ for concept formation? A reply to Richardson & Bhavnani (1984) , 1987 .

[23]  L Sirovich,et al.  Low-dimensional procedure for the characterization of human faces. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[24]  Herv Abdi A Generalized Approach For Connectionist Auto-Associative Memories: Interpretation, Implication Illu , 1988 .

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