Presentation | 2003/11/13 Ethnicity estimation with Facial Image Erina TAKIKAWA, Satoshi HOSOI, Masato KAWADE, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | We have been making efforts to develop vision-based human understanding technologies for realizing human-friendly human machine interfaces. Visual information, such as gender, age, ethnicity, face expression etc., play an important role in face-to-face communication. This paper addresses a novel approach for automatic ethnicity estimation with facial images. In this approach, gabor wavelets transformation and retina sampling are combined to extract key facial features, and support vector machines are used for ethnicity classification. Our system based on this approach achieved classification accuracy of approximately 90% for ethnicity estimation under various illumination conditions. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | facial image / ethnicity estimation / gabor wavelets transformation / support vector machines |
Paper # | PRMU2003-143,HIP2003-49 |
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Committee | HIP |
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Conference Date | 2003/11/13(1days) |
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Registration To | Human Information Processing (HIP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Ethnicity estimation with Facial Image |
Sub Title (in English) | |
Keyword(1) | facial image |
Keyword(2) | ethnicity estimation |
Keyword(3) | gabor wavelets transformation |
Keyword(4) | support vector machines |
1st Author's Name | Erina TAKIKAWA |
1st Author's Affiliation | Vision Sensing Technologies, Sensing Technology Laboratory, OMRON Corporation() |
2nd Author's Name | Satoshi HOSOI |
2nd Author's Affiliation | Vision Sensing Technologies, Sensing Technology Laboratory, OMRON Corporation |
3rd Author's Name | Masato KAWADE |
3rd Author's Affiliation | Vision Sensing Technologies, Sensing Technology Laboratory, OMRON Corporation |
Date | 2003/11/13 |
Paper # | PRMU2003-143,HIP2003-49 |
Volume (vol) | vol.103 |
Number (no) | 454 |
Page | pp.pp.- |
#Pages | 6 |
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