| Alternate document: Details On learning to recognize 3D objects from examples (91) Shimon Edelman |
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Abstract: We describe an implemented system that learns to recognize human faces under varying pose and illumination conditions. The system relies on symmetry operations to detect the eyes and the mouth in a face image, uses the locations of these features to normalize the appearance of the face, performs simple but effective dimensionality reduction by a convolution with a set of Gaussian receptive fields, and subjects the vector of activities of the receptive fields to a Radial Basis Function... (Update)
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.... dimensionality reduction implemented by such a two stage system include the improvement of about 20 in the recognition performance (Edelman et al. 1992); this approach should have a similar effect on the performance of the present model. 6 Summary and discussion We have...
...and physical parameter spaces. A number of systems based on a Radial Basis Function (RBF) network have been proposed for this approach [5, 1, 8]. They showed successful learning capability, and made these variations explicit. However, the generalization capabilities of such...
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BibTeX entry: (Update)
Edelman, S., Reisfeld, D. & Yeshurun, Y. (1992), Learning to recognize faces from examples, in `2nd European Conference on Computer Vision', Genoa, Italy, pp. 787--791. http://citeseer.ist.psu.edu/edelman91learning.html More
@inproceedings{ edelman92learning,
author = "Shimon Edelman and Daniel Reisfeld and Yehezkel Yeshurun",
title = "Learning to Recognize Faces from Examples",
booktitle = "European Conference on Computer Vision",
pages = "787-791",
year = "1992",
url = "citeseer.ist.psu.edu/edelman91learning.html" }
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