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231223s2005 xx ||||| 00| ||eng c |
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|a pubmed24n0532.xml
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|a (DE-627)NLM159573009
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|a (NLM)16355663
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|a DE-627
|b ger
|c DE-627
|e rakwb
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| 041 |
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|a eng
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| 100 |
1 |
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|a Kim, Jongsun
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Effective representation using ICA for face recognition robust to local distortion and partial occlusion
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| 264 |
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1 |
|c 2005
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| 336 |
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|a Text
|b txt
|2 rdacontent
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| 337 |
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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| 338 |
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|a Band
|b nc
|2 rdacarrier
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| 500 |
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|a Date Completed 19.01.2006
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| 500 |
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|a Date Revised 15.11.2006
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| 500 |
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|a published: Print
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|a Citation Status MEDLINE
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| 520 |
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|a The performance of face recognition methods using subspace projection is directly related to the characteristics of their basis images, especially in the cases of local distortion or partial occlusion. In order for a subspace projection method to be robust to local distortion and partial occlusion, the basis images generated by the method should exhibit a part-based local representation. We propose an effective part-based local representation method named locally salient ICA (LS-ICA) method for face recognition that is robust to local distortion and partial occlusion. The LS-ICA method only employs locally salient information from important facial parts in order to maximize the benefit of applying the idea of "recognition by parts." It creates part-based local basis images by imposing additional localization constraint in the process of computing ICA architecture I basis images. We have contrasted the LS-ICA method with other part-based representations such as LNMF (Localized Nonnegative Matrix Factorization) and LFA (Local Feature Analysis). Experimental results show that the LS-ICA method performs better than PCA, ICA architecture I, ICA architecture II, LFA, and LNMF methods, especially in the cases of partial occlusions and local distortions
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| 650 |
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|a Journal Article
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| 650 |
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4 |
|a Research Support, Non-U.S. Gov't
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| 700 |
1 |
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|a Choi, Jongmoo
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Yi, Juneho
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Turk, Matthew
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 27(2005), 12 vom: 19. Dez., Seite 1977-81
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnns
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| 773 |
1 |
8 |
|g volume:27
|g year:2005
|g number:12
|g day:19
|g month:12
|g pages:1977-81
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| 912 |
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| 912 |
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|a GBV_ILN_350
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| 951 |
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|a AR
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| 952 |
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|d 27
|j 2005
|e 12
|b 19
|c 12
|h 1977-81
|