Presentation | 2010-02-15 Automatic Detection of Human Beings in an Image by Using Feature Map Hiroki TAKIGUCHI, Junji MAEDA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | The purpose of this paper is the automatic detection of human beings in a static image. We propose the method of human detection by using the feature map based on the visual attention model. The proposed algorithm uses the features of orientation and gradient magnitude for human detection. We also propose to use the symmetric filter to incorporate bilateral symmetry of human. The use of Gaussian pyramids for making the feature map enables the detection of the most salient feature location. Finally, the human detection is performed by using the human feature map, that is obtained by integrating each feature, and nonlinear support vector machines. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Visual attention model / feature extraction / human feature map / support vector machine / human detection |
Paper # | ITS2009-54,IE2009-148 |
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Committee | ITS |
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Conference Date | 2010/2/8(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Intelligent Transport Systems Technology (ITS) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Automatic Detection of Human Beings in an Image by Using Feature Map |
Sub Title (in English) | |
Keyword(1) | Visual attention model |
Keyword(2) | feature extraction |
Keyword(3) | human feature map |
Keyword(4) | support vector machine |
Keyword(5) | human detection |
1st Author's Name | Hiroki TAKIGUCHI |
1st Author's Affiliation | Division of Computer Science and Systems Engineering, Graduate School of Engineering, Muroran Institute of Technology() |
2nd Author's Name | Junji MAEDA |
2nd Author's Affiliation | Division of Computer Science and Systems Engineering, Graduate School of Engineering, Muroran Institute of Technology |
Date | 2010-02-15 |
Paper # | ITS2009-54,IE2009-148 |
Volume (vol) | vol.109 |
Number (no) | 414 |
Page | pp.pp.- |
#Pages | 6 |
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