| Project/Area Number |
17H01809
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Kansei informatics
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| Research Institution | Kanagawa Institute of Technology (2018-2019)
Kanagawa University (2017) |
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Principal Investigator |
Uchikawa Keiji 神奈川工科大学, 公私立大学の部局等, 客員教授 (00158776)
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| Co-Investigator(Kenkyū-buntansha) |
永井 岳大 東京工業大学, 工学院, 准教授 (40549036)
増田 修 新潟医療福祉大学, 医療技術学部, 教授 (90775967)
吉澤 達也 神奈川大学, 人間科学部, 教授 (90267724)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥17,810,000 (Direct Cost: ¥13,700,000、Indirect Cost: ¥4,110,000)
Fiscal Year 2019: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2018: ¥8,320,000 (Direct Cost: ¥6,400,000、Indirect Cost: ¥1,920,000)
Fiscal Year 2017: ¥7,280,000 (Direct Cost: ¥5,600,000、Indirect Cost: ¥1,680,000)
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| Keywords | 質感知覚 / 色覚 / 色彩工学 / 視覚心理物理学 / 統合質感生起モデル / 脳波計測 |
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| Outline of Final Research Achievements |
Appearance of materials is determined by the integration of their surface attributions, such as color, gloss, and texture (integrated material perception). The integrated material perception is essential to determine surface appearance of objects in the real world although the integrated material perception has not been extensively studied. Observers estimated differences in the integrated material perception for real object images which differed in color and gloss. Our prediction model, using lower-order image statistics, showed a high correlation with the subjective estimation of the differences. Furthermore, we measured estimation in appearance differences in color only and gloss only for the same object images. As results, we obtained that the integrated material perception is simply expressed as linear summation of color and gloss difference estimations.
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| Academic Significance and Societal Importance of the Research Achievements |
これまで独立に扱われてきた物体表面の色や光沢といった質感要素が統合されて生まれる統合質感を定量化し、その生起モデルを構築したこと、およびその結果から物体表面の質感知覚のメカニズムを明らかにしたことは学術的意義が大きい。また、統合質感の予測式を求めたことは質感を定量的に工業製品に反映させようとする製品技術の開発に貢献するものであり、この点、この研究成果の社会的な意義がある。
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