Representation of Spatio-tempral Patterns with Nonlinear Manifold and its Application to Gestrue Recognition
| Project/Area Number |
23700271
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Sensitivity informatics/Soft computing
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| Research Institution | Kyushu Institute of Technology |
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Principal Investigator |
HORIO Keiichi 九州工業大学, 大学院・生命体工学研究科, 准教授 (70363413)
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| Project Period (FY) |
2011 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
Fiscal Year 2012: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2011: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 時空間バターン認識 / マニフォールド / 近似 / 高階自己組織化マツブ / 自己組織化マップ / 非線形マニフォールド / グラフ距離 / ジェスチャ認識 / 学習パラメータ / 時空間パターン / 特徴空間 / マニフォールド学習 |
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| Research Abstract |
Spatio-temporal patterns is considered as a set of feature vectors in a feaure space called as a manifold . In this study，the manifolds were adequately approximated using graph distance based self-organizing map (GSOM)，furthermore，similarity between manifolds represent peculiar forms，and the learning of higher rank SOM often becomes unstable. The learning algorithm was modified to realize a stable learning.
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Report
(3 results)
Research Products
(13 results)
