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ID 30062
FullText URL
Author
Sakaue, Fumihiko
Abstract

Image correction is discussed for realizing both effective object recognition and realistic image-based rendering. Three image normalizations are compared in relation with the linear subspaces and eigenspaces, and we conclude that normalization by L1-norm, which normalizes the total sum of intensities, is the best for our purposes. Based on noise analysis in the normalized image space (NIS), an image correction algorithm is constructed, which is accomplished by iterative projections along with corrections of an image to an eigenspace in NIS. Experimental results show that the proposed method works well for natural images which include various kinds of noise shadows, reflections and occlusions. The proposed method provides a feasible solution to object recognition based on the illumination cone. The technique can also be extended to face detection of unknown persons and registration/recognition using eigenfaces.

Keywords
eigenvalues and eigenfunctions
face recognition
iterative methods
natural scenes
object recognition
rendering (computer graphics)
Note
Digital Object Identifier: 10.1109/ICPR.2002.1044831
Published with permission from the copyright holder. This is the institute's copy, as published in Pattern Recognition, 2002. Proceedings. 16th International Conference on, 11-15 Aug 2002, Vol. 1, Pages 648-651.
Publisher URL:http://dx.doi.org/10.1109/ICPR.2002.1044831
Copyright © 2002 IEEE. All rights reserved.
Published Date
2002-08-11
Publication Title
Pattern Recognition
Volume
volume1
Start Page
648
End Page
651
Content Type
Journal Article
language
英語
Refereed
True
DOI
Submission Path
industrial_engineering/32