2013 Fiscal Year Final Research Report
Construction of categorical color perception model and application for intelligent camera system
| Project/Area Number |
24700159
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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 |
Perception information processing/Intelligent robotics
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| Research Institution | Chiba University |
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Principal Investigator |
YATA Noriko 千葉大学, 融合科学研究科(研究院), 助教 (60528412)
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| Project Period (FY) |
2012-04-01 – 2014-03-31
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| Keywords | 色認識 / 色恒常性 / ニューラルネットワーク |
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| Research Abstract |
Automatic color recognition technology that can correctly discriminate a categorical color in various environments like a human is required. If we want to make a computer vision system able to recognize color like a human, we must consider human visual characteristics such as categorical color perception and color constancy in the color recognition system. To create the model, the relationship between chromaticity of color chips under different illuminations and categorical color perception of the color chips under these illuminations by a human has be learned using a structured neural network.
We propose a new model with modified training data for high recognition performance and perception of multiple colors. In addition, this study proposes a method of recognition of object colors under varying illumination condition in video. The recognition function is the categorical color perception model, and it use the depth information from RGB-D camera.
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