| Presentation | 2005-06-17 An Efficient Feature Selection Method For Object Detection Duy Dinh LE, Shinichi SATOH, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Feature selection is one of the important tasks in many object detection systems because it can improve performance and speed of classifiers. In this paper, we present a simple yet efficient feature selection method based on principle component analysis (PCA) for SVM-based classifiers. The idea is to select features whose corresponding axes are closest to principle components computed from data distribution by PCA. Experimental results show that our proposed method reduces dimensionality similar to PCA but maintains the original measurement meanings while decreasing the computation time significantly. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | feature selection / object detection / face detection / PCA / SVM |
| Paper # | DE2005-22,PRMU2005-43 |
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| Conference Information | |
| Committee | DE |
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| Conference Date | 2005/6/10(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Data Engineering (DE) |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | An Efficient Feature Selection Method For Object Detection |
| Sub Title (in English) | |
| Keyword(1) | feature selection |
| Keyword(2) | object detection |
| Keyword(3) | face detection |
| Keyword(4) | PCA |
| Keyword(5) | SVM |
| 1st Author's Name | Duy Dinh LE |
| 1st Author's Affiliation | The Graduate University for Advanced Studies() |
| 2nd Author's Name | Shinichi SATOH |
| 2nd Author's Affiliation | The Graduate University for Advanced Studies:National Institute of Informatics |
| Date | 2005-06-17 |
| Paper # | DE2005-22,PRMU2005-43 |
| Volume (vol) | vol.105 |
| Number (no) | 117 |
| Page | pp.pp.- |
| #Pages | 4 |
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