This paper describes qualitative and quantita- tive analysis of color emotion dimension expression using a standard device-independent colorimetric system. To collect color emotion data, 20 subjects are required to re...This paper describes qualitative and quantita- tive analysis of color emotion dimension expression using a standard device-independent colorimetric system. To collect color emotion data, 20 subjects are required to report their emotion responses, using a valence-arousal emotion model, to 52 color samples that are chosen from CIELAB Lch color spaces. Qualitative analysis, including analysis of variance （ANOVA）, Pearson＇s correlation and Spearman＇s rank cor- relation, shows that significant differences exist between re- sponses to achromatic and chromatic stimuli, but there are no significant differences between chromatic samples. There is a positive linear relationship between lightness/chroma and valence-arousal dimensions. Subsequently, several clas- sic predictors are used to quantitatively predict emotion in- duced by color attributes. Furthermore, several explicit color emotion models are developed by using multiple linear re- gression with stepwise and pace regression. Experimental results show that chroma and lightness have stronger effects on emotions than hue, which is consistent with our qualitative results and other psychological studies. Arousal has greater predictive value than valence.展开更多
文摘This paper describes qualitative and quantita- tive analysis of color emotion dimension expression using a standard device-independent colorimetric system. To collect color emotion data, 20 subjects are required to report their emotion responses, using a valence-arousal emotion model, to 52 color samples that are chosen from CIELAB Lch color spaces. Qualitative analysis, including analysis of variance （ANOVA）, Pearson＇s correlation and Spearman＇s rank cor- relation, shows that significant differences exist between re- sponses to achromatic and chromatic stimuli, but there are no significant differences between chromatic samples. There is a positive linear relationship between lightness/chroma and valence-arousal dimensions. Subsequently, several clas- sic predictors are used to quantitatively predict emotion in- duced by color attributes. Furthermore, several explicit color emotion models are developed by using multiple linear re- gression with stepwise and pace regression. Experimental results show that chroma and lightness have stronger effects on emotions than hue, which is consistent with our qualitative results and other psychological studies. Arousal has greater predictive value than valence.
