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In this study, to evaluate color emotions and color preferences of cotton fabric having two different colored portions with contrast tones by dyeing with persimmon and indigo, respectively, six different stimuli were prepared with variations of contrasting tone types and color area ratios and they were subjectively assessed by inviting female college students in fashion and textiles. The factor analysis results showed four different factors including 'Light', 'Gentle', 'Traditional', and 'Dynamic' and they were revealed as effected by contrasting tone types such as 'pale-dull' and 'light-dull' and by color area ratios such as 1:1, 2:1, and 1:2 as well as objective colorimetric combination variables. Precisely the type of 'pale-dull' contributed to stronger feeling of factor 'Light' and 'Gentle' and the ratio of 2:1 evoked more perception of 'Light'. Color preference was more highly rated for 'pale-dull' and as Δ a p ∗ as a colorimetric combination variable was higher. Finally color emotion factor such as 'Light' and 'Traditional' and color preference were quantitatively described by modeling each of them with some of objective colorimetric combination variables. [ABSTRACT FROM AUTHOR]

Much research has been done on the relationship between emotions and colors, and many color scheme recommendation tools have been developed. These tools can often help recommend a suitable color scheme to express a certain emotion, but it is still difficult to design satisfying schemes based on such recommendations. In this study, based on the Color Scheme Bible, Compact Edition, we developed Emocolor, which allows professionals to generate a large number of color schemes based on emotional words or emotional images. It is also used to iteratively optimize the generated color schemes based on an interactive genetic algorithm to find the color scheme design that best matches the user's emotion. Through the evaluation of tram color schemes based on emotional words, Emocolor can effectively generate tram color schemes that match users' emotions. It can also effectively transfer the emotion of an image with a single dominant color to a tram color scheme. In short, Emocolor can help professionals describe the relationship between emotion and color in a more accurate way and design emotional color schemes. Emocolor can be applied in advertising design, product design, interior design, and other fields. [ABSTRACT FROM AUTHOR]

This article constructs the hierarchical model of multicolor‐emotion generation network (MCEG‐Net) to investigate human emotional responses to multiple colors based on the research of multicolor perceptual features modeling, which reveals the generation mechanism of multicolor emotion from the perspective of hierarchy of visual features. First, the 164 multicolor samples were evaluated by 30 subjects based on PAD emotion space. On this basis, the correlation analysis was carried out among color basic attributes, multicolor physical features, multicolor perceptual features and emotion. Then, a mathematical model of multicolor emotion was constructed by using multiple linear regression (MLR) algorithm. It was observed that, the multiple colors was strongly correlated with emotion. Finally, the MCEG‐Net was constructed, which reveals the generation mechanism of the process the "the basic attributes of color stimulate human's perceptual reflex and then generate emotion" under the interaction of multiple colors from the perspective of information science. The results showed that the mathematical model could predict color emotion well. In addition, the MCEG‐Net provides a new way to reveal the generation mechanism of color‐emotion associations. [ABSTRACT FROM AUTHOR]

To enhance the emotional communication of image oil painting art and better analyze the image oil painting art, this article puts forward the research on color emotional information communication in image oil painting art. First, starting from the artistic characteristics of color and its embodiment in various oil painting art forms, this article expounds the relationship and the significance between color language and emotional expression. Then, it summarizes the development of color in image oil painting from a macro perspective and analyzes the emotional expression of color in oil painting. Finally, it discusses the color law of the oil painting art and analyzes the emotional expression of the oil painting art from two aspects: image and artistic conception. The research shows that the design method can better convey emotion and make it easier for people to understand the connotation of image oil paintings.

Color harmony is the hotspot of many researchers in the fields of art and design which is widely used in various artworks and design activities. As for psychology, color harmony is closely related to human’s perception and cognition, although, the research of its generation process has not been fully focused on. With experimental psychology with artificial intelligence technology combined together, our aim is to investigate the factors affecting color harmony on the basis of the generation process from perception to cognition, and construct a mathematical model to predict its degree, so as to realize the quantitatively analysis and measurement of color harmony. We classify the factors affecting color harmony into objective and subjective ones. Among them, the objective factors are constructed based on the three principle elements of color with a total of 21-dimensional color-pair objective physical features extracted. And the subjective factors are divided into direct psychological effects and indirect psychological effects. 180 two-color combinations were evaluated by 30 subjects based on color harmony and its subjective factors on discrete scales ranging from −2 to 2. Correlation analysis reveals that color harmony is not only affected by objective factors, but also by subjective factors which has a stronger correlation than that of the objective ones. Finally, machine learning algorithms were adopted to construct a mathematical model, which has been proved that the linear relationship can well explain the generation mechanism of color harmony.

One of the most important challenges in the field of affective computing is the collection of databases from human color-based affective responses. This multimedia database has many applications in anthropology, sociology, psychology, computer, and graphics. However, researches have conducted some research on the affective aspect of monochrome images. Unfortunately, a complete and coherent database is not available to researchers right now. In this paper, data collection for multimedia affective response is tailored to images with two adjacent colors. Here, we examined the color parameters luminance, chrominance, and color hue in the images as well as the observers' characteristics such as age, gender, and education level. To this end, the observers obtained a simple and a patterned two-color image by posting images on a website and using the Self-Assessment Manikin (SAM) technique. A total of 171 simple two-color images and 105 patterned two-color images were considered. The total number of observers was 405, and finally, 4757 responses were collected. Finally, by statistically examining the effect of the mentioned parameters on the emotional valence and arousal, we found that lightness, hue, and pattern parameters had the greatest effect on the value of emotions (valence), but arousal was more related to lightness and chrominance parameters. The parameters were lightness and chrominance. This Two-Color Affective Response (TCAR) database is suitable for processing using advanced computer algorithms such as clustering and classification. The entire data collection process, including color selection to make images, getting emotional responses, and evaluation, was fully described. [ABSTRACT FROM AUTHOR]

Multimodal sentiment analysis is an emerging and critical area of research, particularly in the context of social media where users express their emotions through both text and images. However, existing methods that learn common semantic features between visual and textual modalities for multimodal sentiment analysis often overlook the importance of color information, which plays a crucial role in sentiment expression, according to psychology and art theory. This paper proposes a novel model, named ICCI, which aims to enhance multimodal sentiment analysis in social media by integrating color cues, in order to address the limitation in existing approaches. The proposed model leverages both the semantic information from image-text pairs and the color cues from images to improve the accuracy of sentiment analysis. The model comprises a feature extraction module that extracts semantic features from both images and text, as well as color features from images. Furthermore, the feature interaction module employs a cross-attention mechanism to enable the interaction of information between semantic features and color features. Finally, the label prediction module integrates all attention features to enhance multimodal sentiment analysis. The proposed model was evaluated through experiments on two widely used benchmark datasets, namely MVSA-Single and MVSA-Multiple datasets, demonstrating its effectiveness in outperforming existing methods. On MVSA-Single, ICCI achieved an accuracy of 79.33%. Similarly, on MVSA-Multiple, ICCI achieved an accuracy of 73.29%. The results underscore the importance of integrating color information for more accurate sentiment analysis in social media. [ABSTRACT FROM AUTHOR]

The hue perception and 'warm‐cool' feelings were investigated, in response to various lighting settings, following the adaptation to either 3500K or 5000K to compare which one—between conventional iso‐Correlated Color Temperature (CCT) and a new one based on CIE u'v′ color space—is more compatible with the visual perception. Twenty participants evaluated hue and warm‐cool feelings for 48 test lighting settings, by observing an empty gray booth. The results showed that yellow‐blue and 'warm‐cool' feelings are closely located around the Planckian locus, while red‐green roughly follows the line orthogonal to the Planckian locus in CIE u'v′ color space, at both 3500 K and 5000 K settings. This suggests that u'v′ color space correlates better with human perception. [ABSTRACT FROM AUTHOR]

Abstract: This study explored the best color selections to match the benefits of beauty products based on rankings obtained from an experimental perception of different skin care product containers. Gender (64 males, 75 females) and cultural (76 Taiwanese, 63 Malaysians) differences were also compared, aiming to explore color associations and emotional bonding by using psychophysical testing methods. A survey of 205 market samples showed that nearly half of the existing skin care product containers had a white body color. White appeared frequently on containers for skin whitening, firming, exfoliating, antiaging, and antiacne products. However, skin moisturizing products used an equal amount of white and blue on their containers. The psychophysical experiment results showed that participants felt that white best matched skin whitening products, red matched skin firming and antiaging products, blue matched skin moisturizing products, black matched exfoliating products, and green matched antiacne products. Neither gender nor cultural differences were found to be significant. Comparing the results with color emotion studies, it was found that (1) for color emotion weight, firming products were related to heaviness, whereas whitening products were connected to lightness; (2) for color emotion heat, whitening, moisturizing, exfoliating and antiacne products were aligned with coolness; and (3) for color emotion activity, product container colors were not related, except slightly for firming products. These findings suggest that psychological responses to color meaning are context‐ and experience‐dependent, meaning that selection of colors to match beauty benefits is based more on people's expectations of the products than their color emotion response. [ABSTRACT FROM AUTHOR]

Abstract: Color sensations are tied not only to other sensations, but also emotions. There have been many studies on this. One study regarding architectural color showed that colors were associated with mental status; for example, red relates to arousal, excitation, and stimulus. The purpose of the present study is to investigate how colors are evoked by emotions. The emotions were described both by emotional words and by schematic faces. Since facial expressions are accompanied by facial color, facial expressions should relate more closely to facial color than emotional words. Therefore, we used numerous color samples for our experiments to show discrimination sensitivity to stimuli in subtle differences of color. Some associations between colors and emotions were found, and the tendencies of associations were different among emotions. Anger, joy, surprise, sadness, and no emotion were connected to particular colors. The distribution of color responses in sadness was spread among bluish colors. The emotional tendencies, among anger, joy, surprise, and sadness, were similar in the two conditions of our experiment. However, in the schematic face condition, the color responses for all emotions were increased in the skin‐colored samples. Thus, the context of the face elicited the color responses. [ABSTRACT FROM AUTHOR]

It is estimated that inherited red-green color deficiency, which involves both the protan and deutan deficiency types, is common in men. For red-green defective observers, some reddish colors appear desaturated and brownish, unlike those seen by normal observers. Despite its prevalence, few studies have investigated the effects that red-green color deficiency has on the psychological properties of colors (color emotions). The current study investigated the influence of red-green color deficiency on the following six color emotions: cleanliness, freshness, hardness, preference, warmth, and weight. Specifically, this study aimed to: (1) reveal differences between normal and red-green defective observers in rating patterns of six color emotions; (2) examine differences in color emotions related to the three cardinal channels in human color vision; and (3) explore relationships between color emotions and color naming behavior. Thirteen men and 10 women with normal vision and 13 men who were red-green defective performed both a color naming task and an emotion rating task with 32 colors from the Berkeley Color Project (BCP). Results revealed noticeable differences in the cleanliness and hardness ratings between the normal vision observers, particularly in women, and red-green defective observers, which appeared mainly for colors in the orange to cyan range, and in the preference and warmth ratings for colors with cyan and purple hues. Similarly, naming errors also mainly occurred in the cyan colors. A regression analysis that included the three cone-contrasts (i.e., red-green, blue-yellow, and luminance) as predictors significantly accounted for variability in color emotion ratings for the red-green defective observers as much as the normal individuals. Expressly, for warmth ratings, the weight of the red-green opponent channel was significantly lower in color defective observers than in normal participants. In addition, the analyses for individual warmth ratings in the red-green defective group revealed that luminance cone-contrast was a significant predictor in most red-green-defective individuals. Together, these results suggest that red-green defective observers tend to rely on the blue-yellow channel and luminance to compensate for the weak sensitivity of long- and medium-wavelength (L-M) cone-contrasts, when rating color warmth.

Based on a psychophysical experiment, this study aimed to investigate factors that influenced color emotion and color preference, as well as the correlations between color emotion and color preference. Some color chips of Munsell color order system were picked out to supply actual patterns with different sets to evaluate the factors of hue, chroma, lightness, then they were pasted at a baseplate with black and white backgrounds respectively to involve the influences of backgrounds. Thus, in total 6 groups of color patches were prepared, and 18 attributes were chosen for visual assessment, including 16 words to describe color emotion, together with 2 color preference descriptions, so that massive data of observers’ judgments were gathered. Afterwards, a quantitative analysis and a detailed discussion were carried out for each attribute. Moreover, the calculation of Pearson correlation coefficients indicated that backgrounds could influence the perception of color emotion and color preference in a certain degree, and hue played a more important role than chroma and lightness. Further factor analysis revealed that color emotions do not exist in an isolated manner, and color preference could be represented in three orthogonal dimensions. [ABSTRACT FROM AUTHOR]

Artists usually carefully select different colors in artistic work so as to convey special visual and emotional feelings. Color theme extraction techniques can help users to acquire the color styles in an image. However, current color theme extraction methods ignore the emotional factors, and they can only provide a single theme result for an image as well, neither of which meet people's favor on different colors under different mood states. This article introduces the conception of emotional color theme, introduces the color emotion theory into color theme extraction, and proposes a novel emotion color theme extraction framework. To achieve these goals, we perform the theme extraction with emotion value of each pixel instead of color value. The emotional discrepancy is proposed between the colors in the theme to evaluate a color theme quality and prove it with color theme dataset. Then a data driven approach is adopted to optimize the color theme. Different from previous optimizing strategies, we built the emotional relation between the target theme and the candidate theme. Our method can enhance the color editing results of previous methods, e.g., for color transfer our results can demonstrate hierarchical emotions from a single reference image. © 2015 Wiley Periodicals, Inc. Col Res Appl, 41, 513-522, 2016 [ABSTRACT FROM AUTHOR]

A psychophysical experiment was carried out to investigate factors affecting colour preference for Taiwanese floral pattern fabrics, as a case study of object colour preference. A total of 175 test images of Taiwanese fabrics were used as the stimuli presented on a calibrated computer display. The images were generated on the basis of 5 existing Taiwanese fabrics, each manipulated into 35 images by changing the fabric colour. The 35 colours were selected to cover the most frequently used colours for existing Taiwanese fabrics. The 175 test images were assessed by 76 Taiwanese observers in terms of 9 semantic scales, including Taiwanese style/non-Taiwanese style, Japanese style/non-Japanese style, splendid/plain, traditional/modern, active/passive, warm/cool, heavy/light, like/dislike and harmonious/disharmonious. The experimental results reveal two underlying factors: 'Splendidness' and 'Harmony.' The like/dislike response was found to highly correlate with harmonious/disharmonious, but have poor correlation with Taiwanese style/non-Taiwanese style. The study also reveals several factors affecting colour preference for Taiwanese fabrics, including the interaction effect of colour and pattern, observer's general liking for the object, and the effect of user experience. These findings can help develop a more robust, comprehensive theory of object colour preference. © 2015 Wiley Periodicals, Inc. Col Res Appl, 41, 43-55, 2016 [ABSTRACT FROM AUTHOR]

In this paper, a color transfer framework to evoke different emotions for images based on color combinations is proposed. The purpose of this color transfer is to change the 'look and feel' of images, i.e., evoking different emotions. Colors are confirmed as the most attractive factor in images. In addition, various studies in both art and science areas have concluded that other than single color, color combinations are necessary to evoke specific emotions. Therefore, we propose a novel framework to transfer color of images based on color combinations, using a predefined color emotion model. The contribution of this new framework is threefold. First, users do not need to provide reference images as used in traditional color transfer algorithms. In most situations, users may not have enough esthetic knowledge or path to choose desired reference images. Second, because of the usage of color combinations instead of single color for emotions, a new color transfer algorithm that does not require an image library is proposed. Third, again because of the usage of color combinations, artifacts that are normally seen in traditional frameworks using single color are avoided. We present encouraging results generated from this new framework and its potential in several possible applications including color transfer of photos and paintings. [ABSTRACT FROM AUTHOR]

The purpose of this research is to investigate the color appearance and color connotation of unrelated colors. To investigate color appearance (i.e., brightness, colorfulness, and hue) for unrelated colors, 22 observers have answered their color appearance for 50 unrelated color stimuli using the magnitude estimation method. Perceptual data obtained by the experiment is compared with the color attributes data estimated by unrelated-color appearance models, CAM97u and CAM02u. It is found that both models perform reasonably well but the performance of CAM02u is better than that of CAM97u. For investigating color connotation for unrelated colors, 32 observers have judged their color connotation for the 50 unrelated color stimuli using the 10 color connotation scales (i.e., 'Warm - Cool,' 'Heavy - Light,' 'Modern - Classical,' 'Clean - Dirty,' 'Active - Passive,' 'Hard - Soft,' Tense - Relaxed,' 'Fresh - Stale,' 'Masculine - feminine,' and 'like - Dislike'), and semantic differential method is used for measurement. It is found that the color connotation models developed for related colors perform poorly for unrelated colors. Experimental results indicate that brightness attribute is confusing to estimate and does not affect color connotation significantly for unrelated colors. Based on the psychophysical data, new models for 'Warm-Cool', 'Heavy-Light', 'Active-Passive' and 'Hard-Soft' were proposed using CAM02u hue, brightness, and colorfulness. Color connotations for unrelated colors are classified into three categories, which 'Color solidity,' 'Color heat,' and 'Color purity.' © 2013 Wiley Periodicals, Inc. Col Res Appl, 40, 40-49, 2015 [ABSTRACT FROM AUTHOR]

This study aims to investigate the emotional characteristics of various shades of white. The study involved three experiments: Prior to the main experiments, the emotional characteristics of 13 basic colors were evaluated from which four factors, flamboyant, elegant, clear, and soft were extracted to facilitate the evaluation of white in the subsequent experiments. In Experiment I, white was identified to be dominantly more elegant in comparison to the other colors; in Experiment II, the emotional characteristics of 25 shades of white were assessed to derive an equation for predicting the emotional quality based on the color attributes of different shades of white; lastly in Experiment III, 1:1 scale mock-ups of mobile phones, coated with various shades of white as well as different levels of gloss and texture, were employed for further emotional assessment of white products in real-life situations. Consistent tendencies were observed in Experiment II and Experiment III, confirming the validity of the results. In addition, although color was the most dominant element that decided product emotion, gloss and texture were also found to influence the emotional characteristics of products. In conclusion, this study provides empirical evidence on the emotional responses of different shades of white, and supports designers to find an appropriate color for designing white based products. [ABSTRACT FROM AUTHOR]

Semantic-differential data of color emotions for color pairs were collected and examined with factor analysis (FA) and independent component analysis (ICA). The axial orientations of factors cannot be identified by FA, whereas they can be determined by ICA with the intrinsic statistical properties of data such as kurtosis. Three factors or components were extracted by FA and ICA. The factors extracted by FA with the varimax method were consistent with the primary factors: evaluation, activity, and potency. When ICA extracted components with positive kurtosis, the components did not match any of the primary factors. However, the independent components extracted by ICA for negative kurtosis were consistent with the primary factors, and similar to the factors obtained by FA. The results of ICA suggest that the evaluation, activity, and potency factors are independent dimensions in psychological space of color emotions for color pairs. The distributions of the factor scores in FA and the scores of the independent components obtained by ICA for negative kurtosis were not Gaussian, but they had negative kurtosis. These support the use ofICA instead of FA. © 2012 Wiley Periodicals, Inc. Col Res Appl, 38, 297-308, 2013 [ABSTRACT FROM AUTHOR]

This paper describes qualitative and quantitative 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 correlation, shows that significant differences exist between responses 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 classic predictors are used to quantitatively predict emotion induced by color attributes. Furthermore, several explicit color emotion models are developed by using multiple linear regression 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. [ABSTRACT FROM AUTHOR]

Abstract: This article compares color assessments of automotive exteriors at four locations in China, Thailand and Japan. This study employed painted panels of twelve colors, thirty sensory words and fifteen pairs of emotion variables. It also used reference figures of nine cars that included four styling categories, namely sedans, compacts, sport utility vehicles and sports cars. The results of like–dislike tests revealed that basic automotive exterior colors, such as black, white and red, were highly preferred across locations. However, geographical differences are apparent in the preference for some non-basic colors. To elucidate these geographical differences, a Chi-square test and principal component analysis were performed on the data on emotion variables. The results revealed both similarities and differences in color preferences among the four locations. Color preferences were similar in Hong Kong and Shanghai when simply evaluated by color samples. However, similar preferences for automotive exterior colors were observed in Hong Kong, Kyoto and Bangkok, but not in Shanghai. These results suggest that there is fluctuation in the emotion evoked by a color when the color is considered in the context of automotive exteriors. Therefore, this study indicates that automotive sales can be secured in the global marketplace by creating a single palette of exterior colors based on similar color preferences across countries. However, these results also indicate that preparing market-specific automotive-color line-ups can be an effective marketing strategy. [Copyright &y& Elsevier]