Pattern recognition using graph signal processing for large-scale time-sequence data
| Project/Area Number |
15K12061
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Perceptual information processing
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
Koichi Shinoda 東京工業大学, 情報理工学院, 教授 (10343097)
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| Co-Investigator(Kenkyū-buntansha) |
井上 中順 東京工業大学, 情報理工学院, 助教 (10733397)
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2017: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Keywords | 動作認識 / グラフ信号処理 / 深度カメラ / 音声認識 / 映像認識 |
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| Outline of Final Research Achievements |
We have developed an action recognition method from RGB-D camera inputs. This method uses a time sequence of human skeleton as an input. Every frame it extracts features by using spectral graph wavelet transform. Then the features are pooled in a hierarchical way in the time axis. This method achieved the state-of-the-art in multi-view action recognition.
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Report
(4 results)
Research Products
(3 results)
