References
- Adini Y, Moses Y, Ullman S. Face recognition: the problem of compensating for changes in illumination direction. CS-TR 21, Weizmann Institute of Science. 1993
- Atick J J. Could information theory provide an ecological theory of sensory processing?. Network 1992; 3: 213–51
- Atick J J, Redlich A N. What does the retina know about natural scenes?. Neural Comput. 1992; 4: 196–210
- Daugman J G. An information-theoretic view of analog representation in the striate cortex. Computational Neuroscience, E L Schwartz. MIT Press, Cambridge, MA 1988; 403–23
- Davis P J, Rabinowitz P. Methods of Numerical Integration. Academic, New York 1975
- Desimone R, Ungerleider L. Neural mechanisms of visual processing in monkeys. Handbook of Neuropsychology, F Boler, J Grafman. Elsevier, Amsterdam 1989; 2: 267–99
- Edelman S. Representation similarity and the chorus of prototypes. CS-TR 93-10, Weizmann Institute of Science. 1993, (1995 Minds Machines to appear)
- Edelman S, Poggio T. Bringing the grandmother back into the picture: a memory-based biew of object recognition. Int. J. Pattern Recog. Artif. Intell. 1992; 6: 37–62
- Edelman S, Reisfeld D, Yeshurun Y. Learning to recognize faces from examples. Proc. 2nd European Conf. on Computer Vision, G Sandini. Springer, Berlin 1992; 787–91, (Lecture Notes in Computer Science 588)
- Field D J. Relations between the statistics of natural images and the response properties of cortical cells. J. Opt. Soc. Am. A 1987; 4: 2379–94
- Field D J. What is the goal of sensory coding?. Neural Comput. 1994; 6: 559–601
- Freeman W T, Adelson E. The design and use of steerable filters. IEEE Trans. Pattern Anal. Machine Int. 1991; 13: 891–906
- Gibson J J. The Ecological Approach to Visual Perception. Houghton Mifflin, Boston, MA 1979
- Hancock P J B, Baddeley R J, Smith L S. The principal components of natural images. Network 1992; 3: 61–70
- Intrator N, Gold J. Three-dimensional object recognition in gray-level images: the usefulness of distinguishing features. Neural Comput. 1993; 5: 61–74
- Intrator N, Glod J I, Bülthoff H H, Edelman S. Three-dimensional object recognition using an unsupervised neural network: understanding the distinguishing features. Neural Information Processing systems, J Moody, S J Hanson, R L Lippman. Kaufmann, San Mateo, CA 1992; 4: 460–7
- Jones D G, Malik J. A computational framework for determining stereo correspondence from a set of linear spatial filters. Proc. 2nd European Conf. on Computer Vision, G Sandini. Springer, Berlin 1992, (Lecture Notes in Computer Science 588)
- Kruskal J B, Wish M. Multidimensional Scaling. Sage, Beverly Hills, CA 1978
- Kube P, Pentland A. On the imaging of fractal surfaces. IEEE Trans. Pattern Anal. Machine Int. 1988; 10: 704–7
- Marr D. Vision. Freeman, San Francisco, CA 1982
- Moses Y. Computational approaches in face recognition. Feinberg Graduate School of the Weizmann Institute of Science. 1993, PhD thesis
- Moses Y, Ullman S. Limitations of non model-based recognition schemes. Proc. 2nd European Conf. on Computer Vision, G Sandini. Springer, Berlin 1992; 820–8, (Lecture Notes in Computer Science 588)
- Mundy J L, Zisserman A. Geometric Invariance in Computer Vision, J L Mundy, A Zisserman. MIT Press, Cambridge, MA 1992
- O'Toole A, Abdi H, Deffenbacher K, Valentin K. Low-dimensional representation of faces in higher dimensions of the face space. J. Opt. Soc. Am. 1993; 10: 405–10
- Pentland A, Starner T, Etcoff N, Masoiu A, Oliylide O, Turk M. Experiments with eigenfaces. Looking at People Workshop (IJCAI). 1993
- Poggio T, Edelman S. A network that learns to recognize three-dimensional objects. Nature 1990; 343: 263–6
- Ratliff F, Sirovich L. Equivalence classes of visual stimuli. Vision Res. 1978; 18: 845–51
- Shashua A. Illumination and view position in 3D visual recognition. Neural Information Processing Systems, J Moody, S J Hanson, R L Lippman. Kaufmann, San Mateo, CA 1992; 4: 404–11
- Truk M, Pentland A. Eigenfaces for recognition. J. Cognitive Neurosci. 1991; 3: 71–86
- Ullman S, Basri R. Recognition by linear combinations of models. IEEE Trans. Pattern Anal. Machine Intell. 1991; 13: 992–1005