| Presentation | 2008-09-06 Abnormal Motion Detection at Escalator Scene based on Spatio-temporal Features Yasuhiro Murai, Hironobu Fujiyoshi, Masato Kazui, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | This paper presents a method for detecting abnormal motion at an escalator scene, in which the movement of the escalator provides a dynamic background. This method is based on the use of spatio-temporal features obtained by space-time patches. Our approach consists of three steps; dynamic background modeling by using the Gaussian mixture model, human region detection based on RealAdaboost, and calculation of irregularity measure by using weighted space-time gradients. The proposed method can detect abnormal motions from a scene with a dynamic background, that would be difficult to detect with the conventional method using CHLAC (Cubic Higher-order Local Auto-Correlation) features. Our experimental results show that using our method has about 27% higher performance than that of the conventional method. |
| Keyword(in Japanese) | (See Japanese page) |
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| Paper # | PRMU2008-87,HIP2008-87 |
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| Committee | PRMU |
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| Conference Date | 2008/8/29(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| Registration To | Pattern Recognition and Media Understanding (PRMU) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Abnormal Motion Detection at Escalator Scene based on Spatio-temporal Features |
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| 1st Author's Name | Yasuhiro Murai |
| 1st Author's Affiliation | Department of Computer Science, Chubu University() |
| 2nd Author's Name | Hironobu Fujiyoshi |
| 2nd Author's Affiliation | Department of Computer Science, Chubu University |
| 3rd Author's Name | Masato Kazui |
| 3rd Author's Affiliation | Hitachi, Ltd., Hitachi Research Laboratory |
| Date | 2008-09-06 |
| Paper # | PRMU2008-87,HIP2008-87 |
| Volume (vol) | vol.108 |
| Number (no) | 198 |
| Page | pp.pp.- |
| #Pages | 8 |
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