| Presentation | 2012-07-19 Model-Based Human Activity Classification using Doppler Sensor with Support Vector Machine Franck DIRHOLDI, Tomoaki OHTSUKI, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The feasibility of classifying different human activities based on micro Doppler signatures is investigated. We simulate six activities using our own human model. These activities are walking, falling, sitting down, making squats, punching, and picking up an object on the ground. We extract four features from the model generated Doppler spectrogram. We collect data from a human subject performing six activities. A support vector machine (SVM) is then trained using the data extracted from our model. We extract the same data from the Doppler spectrogram obtained during experiments. The activities are correctly detected more than 90 % of the time and falling is detected 100 |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Dopler spectrogram / microDoppler / human activities / human model |
| Paper # | USN2012-19 |
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| Conference Information | |
| Committee | USN |
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| Conference Date | 2012/7/12(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
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| Registration To | Ubiquitous and Sensor Networks(USN) |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Model-Based Human Activity Classification using Doppler Sensor with Support Vector Machine |
| Sub Title (in English) | |
| Keyword(1) | Dopler spectrogram |
| Keyword(2) | microDoppler |
| Keyword(3) | human activities |
| Keyword(4) | human model |
| 1st Author's Name | Franck DIRHOLDI |
| 1st Author's Affiliation | School of Science for Open and Environmental Systems, Graduate School of Science and Technology, Keio University() |
| 2nd Author's Name | Tomoaki OHTSUKI |
| 2nd Author's Affiliation | School of Science for Open and Environmental Systems, Graduate School of Science and Technology, Keio University |
| Date | 2012-07-19 |
| Paper # | USN2012-19 |
| Volume (vol) | vol.112 |
| Number (no) | 133 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |