Color associations in abstract semantic domains

Guilbeault, Douglas; Nadler, Ethan O.; Chu, Mark; Sardo, Donald Ruggiero Lo; Kar, Aabir Abubaker; Desikan, Bhargav Srinivasa

doi:10.1016/j.cognition.2020.104306

Cited by 17 publications

(19 citation statements)

References 29 publications

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“…To do this, they selected one of the nine silhouettes defined by Stunkard et al [ 20 ] and chose to color it in one of the following hues: orange, yellow, red, gray or white. The orange color is associated with fear and anxiety; red with desire, hate and passion; yellow with happiness, joy and love; gray with depression and sadness; and white with neutrality [ 21 , 22 ]. They then rated on 10-point scales either none, one or more of the 20 emotional terms from the Geneva Wheel [ 23 , 24 ].…”

Section: Methodsmentioning

confidence: 99%

Behavioral and Emotional Changes One Year after the First Lockdown Induced by COVID-19 in a French Adult Population

et al. 2022

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(1) Background: The lockdown had various consequences on physical activity and food consumption behaviors. The post-lockdown has been much less studied. The aim of this study is to compare behaviors one year after the first lockdown in a group of normal-weight (NW) or overweight French adults (OW). (2) Methods: Over a period of 4 days, both at the beginning of May 2020 (lockdown) and in June 2021 (free living post-lockdown), the same French adults used the WellBeNet smartphone application to record their sedentary behavior, physical activity (PA), food consumption and emotions. (3) Results: One year post first lockdown, the weight and body mass index increased (+1.1 kg; +0.4 kg.m−2, p < 0.01), and sedentary behaviors increased (+5.5%, p < 0.01) to the detriment of light-intensity activities (−3.3%, p = 0.10) in the whole group. Some food categories, such as alcohol, tended to be consumed more (+0.15 portion/day, p = 0.09), while fatty, salty and sugary products decreased (−0.25 portion/d, p = 0.02) but without a change in the food balance score. A higher number of both positive and negative emotions were scored per day (+9.5, p < 0.0001; +2.9, p = 0.03), and the positive ones were perceived stronger (+0.23, p = 0.09). Simultaneously, the desire to eat was lower (−11.6/100, p < 0.0001), and the desire to move remained constant. Sedentary/active behaviors and the desire to eat changed differently in NW and OW adults after the lockdown. (4) Conclusions: In general, the post-lockdown period was less favorable for physical activity practice and resulted in a similar food balance score but was more conducive to mental wellbeing.

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Section: Methodsmentioning

confidence: 99%

Behavioral and Emotional Changes One Year after the First Lockdown Induced by COVID-19 in a French Adult Population

et al. 2022

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“…Since the 2010s, there has been an explosion in the number of papers exploring art forms using computational methods ([ 5 , 6 , 7 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]). This has been due to the more formal organisation of image-based datasets, and the large-scale use of neural-network- and data-science-based approaches for image analysis.…”

Section: Computation and Artmentioning

confidence: 99%

“…We again note that neural networks do not specifically extract color-based information from images, focusing instead on patterns of pixels and texture [ 8 ]. To ensure that our representations capture multiple aspects of artwork, we measure color information using a state-of-the-art transformation of colorspace that accurately captures human color perception (referred to as a perceptually uniform colorspace ) [ 26 , 35 ]. We use the comp-syn package to extract these color representations [ 27 ], where each artwork is represented by an eight-dimensional color-distributional vector.…”

Section: Wikiartvectors : Vectorisation and Feature Extractionmentioning

confidence: 99%

WikiArtVectors: Style and Color Representations of Artworks for Cultural Analysis via Information Theoretic Measures

Desikan

Shimao

Miton

2022

Entropy

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With the increase in massive digitized datasets of cultural artefacts, social and cultural scientists have an unprecedented opportunity for the discovery and expansion of cultural theory. The WikiArt dataset is one such example, with over 250,000 high quality images of historically significant artworks by over 3000 artists, ranging from the 15th century to the present day; it is a rich source for the potential mining of patterns and differences among artists, genres, and styles. However, such datasets are often difficult to analyse and use for answering complex questions of cultural evolution and divergence because of their raw formats as image files, which are represented as multi-dimensional tensors/matrices. Recent developments in machine learning, multi-modal data analysis and image processing, however, open the door for us to create representations of images that extract important, domain-specific features from images. Art historians have long emphasised the importance of art style, and the colors used in art, as ways to characterise and retrieve art across genre, style, and artist. In this paper, we release a massive vector-based dataset of paintings (WikiArtVectors), with style representations and color distributions, which provides cultural and social scientists with a framework and database to explore relationships across these two vital dimensions. We use state-of-the-art deep learning and human perceptual color distributions to extract the representations for each painting, and aggregate them across artist, style, and genre. These vector representations and distributions can then be used in tandem with information-theoretic and distance metrics to identify large-scale patterns across art style, genre, and artist. We demonstrate the consistency of these vectors, and provide early explorations, while detailing future work and directions. All of our data and code is publicly available on GitHub.

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“…However, there are actually many factors that can influence human perception, and by conducting some psychological and physiological experiments, corresponding general rules can be established as a way to obtain more credible perceptual evaluations. Douglas et al [ 13 ] used a transformation of color space very similar to human color perception to measure color, and found that semantically similar words are similar in color distribution, providing a semantic based on metaphorical perception. By proposing a new approach to interpretation, these works provide some support for color perception research.…”

Section: Introductionmentioning

confidence: 99%

Color Design Decisions for Ceramic Products Based on Quantification of Perceptual Characteristics

Wang

Zhao

Chen

et al. 2022

Sensors

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The appearance characteristics of ceramic color are an important factor in determining the user’s aesthetic perception of the product. Given the problem that ceramic color varies and the user’s visual sensory evaluation of color is highly subjective and uncertain, a method of quantifying ceramic color characteristics based on the Back Propagation (BP) neural network algorithm is proposed. The semantic difference method and statistical method were used to obtain quantified data from ceramic color perceptual semantic features and were combined with a neural network to study the association between ceramic color features and user perceptual-cognitive evaluation. A BP neural network was used to build a ceramic color perceptual semantic mapping model, using color semantic quantified values as the input layer, color L, A, and B component values as the output layer, and model training to predict the sample. The output color L, A, and B components are used as the input layer and the color scheme was designed. The above method can effectively solve the mapping problem between the appearance characteristics of ceramic color and perceptual semantics and provide a decision basis for ceramic product color design. The case application of color design of daily-use ceramic products was conducted to verify the effectiveness and feasibility of the quantitative research method of ceramic color imagery.

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Color associations in abstract semantic domains

Cited by 17 publications

References 29 publications

Behavioral and Emotional Changes One Year after the First Lockdown Induced by COVID-19 in a French Adult Population

Behavioral and Emotional Changes One Year after the First Lockdown Induced by COVID-19 in a French Adult Population

WikiArtVectors: Style and Color Representations of Artworks for Cultural Analysis via Information Theoretic Measures

Color Design Decisions for Ceramic Products Based on Quantification of Perceptual Characteristics

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