| Presentation | 2006-05-26 Detecting the Degree of Anomal in Security Videos by using a Spatio-temporal Feature of Change Kyoko SUDO, Tatsuya OSAWA, Kaoru WAKABAYASHI, Takayuki YASUNO, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The method to discriminate anomalous image sequences for efficiently watching monitoring videos is proposed. Considering of applying systems composed of many monitoring cameras, the method is required which is independent of the camera setting environment and the contents of the videos. We propose a method that can discriminate anomalous image sequences for more efficiently utilizing security videos. Considering the wide popularity of security cameras, the method is independent of the camera setting environment and the contents of the videos. We use the spatio-temporal feature obtained by extracting the areas of change from the video. To create the input for the discrimination process, we reduce the dimensionality of the data by PCA. Discrimination is based on a 1-class SVM, which is a non-supervised learning method, and its output is the degree of anomaly of the sequence. The method is applied to videos that simulate real environments and the results show the feasibility of determining anomalous sequences from security videos. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | security video / anomal detection / 1-class SVM |
| Paper # | PRMU2006-28,MI2006-28 |
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| Conference Information | |
| Committee | PRMU |
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| Conference Date | 2006/5/19(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| 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) | Detecting the Degree of Anomal in Security Videos by using a Spatio-temporal Feature of Change |
| Sub Title (in English) | |
| Keyword(1) | security video |
| Keyword(2) | anomal detection |
| Keyword(3) | 1-class SVM |
| 1st Author's Name | Kyoko SUDO |
| 1st Author's Affiliation | NTT Cyber Space Laboratories, NTT Corporation() |
| 2nd Author's Name | Tatsuya OSAWA |
| 2nd Author's Affiliation | NTT Cyber Space Laboratories, NTT Corporation |
| 3rd Author's Name | Kaoru WAKABAYASHI |
| 3rd Author's Affiliation | NTT Cyber Space Laboratories, NTT Corporation |
| 4th Author's Name | Takayuki YASUNO |
| 4th Author's Affiliation | NTT Cyber Space Laboratories, NTT Corporation |
| Date | 2006-05-26 |
| Paper # | PRMU2006-28,MI2006-28 |
| Volume (vol) | vol.106 |
| Number (no) | 73 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |