2006 Fiscal Year Final Research Report Summary
Computing with Words for Understanding and Generation of Modal Human Motions affected by Mental and Physical Conditions
| Project/Area Number |
16500123
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Sensitivity informatics/Soft computing
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| Research Institution | Nagaoka University of Technology |
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Principal Investigator |
NAKAMURA Kazuo Nagaoka University of Technology, Faculty of Engineering, Professor, 工学部, 教授 (40272869)
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| Project Period (FY) |
2004 – 2006
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| Keywords | motion understanding / motion generation / mental and physical conditions / linguistic category / computing / eigen-space method / hidden Markov model / Choquet integral agent networks |
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| Research Abstract |
In everyday human motions they can express primary objective motions with secondary modification motions affected by their mental and/or physical conditions at any moment. For realizing human friendly interactive systems, introduction of human interfaces using body motion understanding and/or generation is crucial.
This study proposes a conceptual frameworks on human interfaces using human motions for man-intellectual machine systems, and shows the ways to realize the mechanisms mentioned below.
1) "Human mimetic cognitive mechanisms for understanding human motions" From human motions it can not only distinct the primary motions but also understand the affective mental and physical conditions from the secondly modification motions.
2) "Motion modification mechanisms of virtual mannequins" It makes intellectual machines generate not only the primary objective motions but also the secondly motions of the virtual mannequins which are embedded certain mental and physical conditions.
The presen
… More
t approach to these mechanisms employs the concept computing with words to capture human action objectives and uncertain mental and physical conditions as human comprehensible semantic complexes. To realize more specifically mutual transformations among physical motion features, linguistic categories for modal motions, and linguistic categories for mental and physical conditions in this approach, it employs some specific soft computing procedures, i.e., parametric eigen-space methods, hidden Markov models, Choquet integral agent networks, and GA.
To verify the effectiveness of the approach some experiments were conducted, where the subjects played the several given everyday motions with several given modal modifications. The experimental data measured by a 3D motion capture system were applied to the proposed mechanisms computing with words. Then the estimated motion modalities were confirmed to be rather valid concerning the human mimetic cognitive mechanisms for understanding human motions. And the generated motions of virtual mannequin were confirmed to be adequate concerning the motion modification mechanisms for several given primary motions with several given modal modifications. Less
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