The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Face recognition: the problem of compensating for changes in illumination direction
Abstract
A face recognition system must recognize a face from a novel image despite the variations between images of the same face. A common approach to overcoming image variations because of changes in the illumination conditions is to use image representations that are relatively insensitive to these variations. Examples of such representations are edge maps, image intensity derivatives, and images convolved with 2D Gabor-like filters. Here we present an empirical study that evaluates the sensitivity of these representations to changes in illumination, as well as viewpoint and facial expression. Our findings indicated that none of the representations considered is sufficient by itself to overcome image variations because of a change in the direction of illumination. Similar results were obtained for changes due to viewpoint and expression. Image representations that emphasized the horizontal features were found to be less sensitive to changes in the direction of illumination. However, systems based only on such representations failed to recognize up to 20 percent of the faces in our database. Humans performed considerably better under the same conditions. We discuss possible reasons for this superiority and alternative methods for overcoming illumination effects in recognition.
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Cites
A Computational Approach to Edge Detection
Canny, J. (1986) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1986.4767851 · Cited by 30,004
Turk, M., & Pentland, A. (1991) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1991.3.1.71 · Cited by 13,733
Marr, D., & Hildreth, E. (1980) · Proceedings of the Royal Society of London. Series B. Biological Sciences · doi:10.1098/rspb.1980.0020 · Cited by 6,510
Daugman, J. G. (1985) · Journal of the Optical Society of America A · doi:10.1364/josaa.2.001160 · Cited by 3,219
Cited by
Daugman, J. (2004) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2003.818350 · Cited by 2,927
The CAS-PEAL large-scale chinese face database and baseline evaluations
Gao, W., Cao, B., Shan, S., Chen, X., Zhou, D., Zhang, X., & Zhao, D. (2008) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/tsmca.2007.909557 · Cited by 773
A review on Gabor wavelets for face recognition
Shen, L., & Bai, L. (2006) · Pattern Analysis and Applications · doi:10.1007/s10044-006-0033-y · Cited by 462
A unified framework for subspace face recognition
Wang, X., & Tang, X. (2004) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2004.57 · Cited by 359
Comparing face recognition algorithms to humans on challenging tasks
O'Toole, A. J., An, X., Dunlop, J., Natu, V., & Phillips, P. J. (2012) · ACM Transactions on Applied Perception · doi:10.1145/2355598.2355599 · Cited by 45
Metadata
- Authors
- Adini, Y., Moses, Y., & Ullman, S.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1997-07
- Volume
- 19
- Issue
- 7
- Pages
- 721-732
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2144143728
- Cited by
- 1,059
- References
- 4
- FWCI
- 12.62
- Type
- journal article
- Language
- en
- Open access
- closed
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- Adini, Y., Moses, Y., & Ullman, S. (1997). Face recognition: the problem of compensating for changes in illumination direction. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/34.598229
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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