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Adding Texture to Color


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Title Adding Texture to Color
Subtitle Quantitative Analysis of Color Emotions
Title of Series The 5th European Conference on Colour in Graphics, Imaging, and Vision and the 12th International Symposium on Multispectral Colour Science (CGIV 2010/MCS'10)
Part Number 2
Number of Parts 43
Author Lucassen, Marcel P.
Gevers, Theo
Gijsenij, Arjan
License CC Attribution - NoDerivatives 2.0 UK: England & Wales:
You are free to use, copy, distribute and transmit the work or content in unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
DOI 10.5446/18246
Publisher River Valley TV
Release Date 2011
Language English
Production Place Joensuu, Finland

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Subject Area Computer Science
Abstract What happens to color emotion responses when texture is added to color samples? To quantify this we performed an experiment in which subjects ordered samples (displayed on a computer monitor) along four scales: Warm-Cool, Masculine-Feminine, Hard-Soft and Heavy-Light. Three sample types were used: uniform color, grayscale textures and color textures. Ten subjects arranged 315 samples (105 per sample type) along each of the four scales. After one week, they repeated the full experiment. The effect of adding texture to color samples is that color remains dominant for the Warm-Cool, Heavy-Light and Masculine-Feminine scale (in order of descending dominance), the importance of texture increases in that same order. The Hard-Soft scale is fully dominated by texture. The average intra-observer variability (between the first and second measurement) was 0.73, 0.66 and 0.65 for the uniform color, grayscale texture and color texture samples, respectively. The average inter-observer variability (between an observer and the other observers) was 0.68, 0.77 and 0.65, respectively. Using some 25,000 observer responses, we derived analytical functions for each sample type and emotion scale (except for the Warm-Cool scale on grayscale textures). These functions predict the group-averaged scale responses from the samples’ color and texture parameters. For uniform color samples, the accuracy of our functions is significantly higher (average adjusted R2 = 0.88) than that of functions previously reported. For color texture, the average adjusted R2=0.80.
Keywords The 5th European Conference on Colour in Graphics, Imaging
Vision and the 12th International Symposium on Multispectral Colour Science

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