| Presentation | 2013-01-23 Face model creation based on simultaneous execution of hierarchical training-set clustering and common local feature extraction Takayuki FUKUI, Toshikazu WADA, Hiroshi OIKE, Jun SAKATA, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Face image retrieval based on local features has advantages of short elapsed time and robustness against the occlusions. However, the keypoint detection, beforehand with the feature descnption, may fail due to illumination change. For solving this problem, top-down model-based keypoint detection must be effective, where man-made face model does not fit for this task. This report addresses the problem of bottom-up face model creation from examples, which can be formalized as common local feature extraction among examples. For this purpose, a measure called Diverse Density (DD) established in the field of Multiple Instance Learning (MIL) can be applied. DD at a point in a feature space represents how the point is close to other positive examples while keeping enough distance from negative examples. Because of this this property, DD is defined as a product of metrics, which can easily be affected by exceptional data, i.e., if one negative data leaps into the neighbor of a positive example, the DD around there becomes lower. Actually, face images have wide vanations of face organs' positions, beard, mustache, glasses, and so on. Under these vanations, DD for wide varieties of face images will be low at any point in the feature point. For solving this problem, we propose a method performing hierarchical clustering and common feature extraction simultaneously. In this method, DD score is employed as a measure representing the integrity of the face image set, and hierarchical clustering is performed by merging the cluster pair having maximum DD score. Through experiments on 1021 CASPEAL face images, we confirmed that multiple face models are successfully constructed. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Multiple Instance Learning / Diverse Density / hierarchical clustering / common image features |
| Paper # | PRMU2012-84,MVE2012-49 |
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| Conference Information | |
| Committee | MVE |
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| Conference Date | 2013/1/16(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Media Experience and Virtual Environment (MVE) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Face model creation based on simultaneous execution of hierarchical training-set clustering and common local feature extraction |
| Sub Title (in English) | |
| Keyword(1) | Multiple Instance Learning |
| Keyword(2) | Diverse Density |
| Keyword(3) | hierarchical clustering |
| Keyword(4) | common image features |
| 1st Author's Name | Takayuki FUKUI |
| 1st Author's Affiliation | Faculty of Systems Engineering, Wakayama University() |
| 2nd Author's Name | Toshikazu WADA |
| 2nd Author's Affiliation | Faculty of Systems Engineering, Wakayama University |
| 3rd Author's Name | Hiroshi OIKE |
| 3rd Author's Affiliation | Faculty of Systems Engineering, Wakayama University |
| 4th Author's Name | Jun SAKATA |
| 4th Author's Affiliation | Faculty of Systems Engineering, Wakayama University |
| Date | 2013-01-23 |
| Paper # | PRMU2012-84,MVE2012-49 |
| Volume (vol) | vol.112 |
| Number (no) | 386 |
| Page | pp.pp.- |
| #Pages | 6 |
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