Presentation | 2013-09-02 Study on Illumination Insensitive Face Detection Based on Normalization Techniques Min YAO, Hiroshi NAGAHASHI, |
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Abstract(in English) | Face detection has been attracting much academic attention. Illumination problem is one of the most important aspects that decreases its performance. Conventional methods have focused on extracting illumination invariant features or utilizing skin color information. However, the features and colors are unreliable in adverse lighting conditions. In this paper, we investigate various illumination normalization techniques for learning-based face detection under varying illumination. They are four illumination insensitive face representation techniques and five histogram-based normalization methods including our proposed method SH (segmentation-based HHTS). The experimental results show that 1) effective illumination normalization techniques in face recognition are not necessarily useful in face detection; 2) histogram-based methods significantly outperform illumination insensitive face representation techniques in average; 3) SH obtains the best results. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Face Detection / Illumination Normalization / Learning-based / Illumination Insensitive |
Paper # | PRMU2013-33,IBISML2013-13 |
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Conference Information | |
Committee | PRMU |
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Conference Date | 2013/8/26(1days) |
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Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Study on Illumination Insensitive Face Detection Based on Normalization Techniques |
Sub Title (in English) | |
Keyword(1) | Face Detection |
Keyword(2) | Illumination Normalization |
Keyword(3) | Learning-based |
Keyword(4) | Illumination Insensitive |
1st Author's Name | Min YAO |
1st Author's Affiliation | Department of Information Processing, Tokyo Insitute of Technology() |
2nd Author's Name | Hiroshi NAGAHASHI |
2nd Author's Affiliation | Imaging Science and Engineering Laboratory, Tokyo Institute of Technology |
Date | 2013-09-02 |
Paper # | PRMU2013-33,IBISML2013-13 |
Volume (vol) | vol.113 |
Number (no) | 196 |
Page | pp.pp.- |
#Pages | 6 |
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