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We introduce a novel dataset of affective, semantic, and descriptive norms for all facial emojis at the point of data collection. We gathered and examined subjective ratings of emojis from 138 German speakers along five essential dimensions: valence, arousal, familiarity, clarity, and visual complexity. Additionally, we provide absolute frequency counts of emoji use, drawn from an extensive Twitter corpus, as well as a much smaller WhatsApp database. Our results replicate the well-established quadratic relationship between arousal and valence of lexical items, also known for words. We also report associations among the variables: for example, the subjective familiarity of an emoji is strongly correlated with its usage frequency, and positively associated with its emotional valence and clarity of meaning. We establish the meanings associated with face emojis, by asking participants for up to three descriptions for each emoji. Using this linguistic data, we computed vector embeddings for each emoji, enabling an exploration of their distribution within the semantic space. Our description-based emoji vector embeddings not only capture typical meaning components of emojis, such as their valence, but also surpass simple definitions and direct emoji2vec models in reflecting the semantic relationship between emojis and words. Our dataset stands out due to its robust reliability and validity. This new semantic norm for face emojis impacts the future design of highly controlled experiments focused on the cognitive processing of emojis, their lexical representation, and their linguistic properties. [ABSTRACT FROM AUTHOR]

Liaoning terminal and Beijing railway station are significant architectural heritage sites along the Peking–Mukden Railway. Their architectural styles do not only embody their cultural value but also serve as their carriers. This study explores the relationship between the architectural styles of these two stations and their geometric characteristics to uncover the origins and underlying principles of their styles, thereby contributing to their preservation and renovation. By analyzing the geometric systems, order of plans and elevations, and the visual complexity of their elevations, the study provides valuable insights. The classical attributes of these stations are manifested through the use of geometric proportion systems with a considerable fractal dimension, demonstrating continuity across different scales. Conversely, their modernity and national style are reflected in the intricate elevation elements, which exhibit varying fractal dimensions across different elevation layers. [ABSTRACT FROM AUTHOR]

Visual complexity is a crucial criterion for evaluating the quality of urban environments and a key dimension in arousal theory and visual preference theory. Objectively quantifying visual complexity holds significant importance for decision-making support in urban planning. This study proposes a visual complexity quantification model based on a support vector machine (SVM), incorporating six key indicators, to establish a mapping relationship between objective image features and subjective complexity perception. This model can efficiently and scientifically predict street view complexity on a large scale. The research findings include the following: (1) the introduction of a new quantification dimension for the urban environment complexity—hierarchical complexity– which reflects the richness of street elements based on an in-depth semantic understanding of images; (2) the established complexity quantification model demonstrates high accuracy, with the indicators ranked by contribution for compression ratio, grayscale contrast, hierarchical complexity, fractal dimension, color complexity, and symmetry; and (3) the model was applied to predict and analyze the visual complexity of the Xiaobailou and Wudadao Districts in Tianjin, revealing that the visual complexity of most streets is moderate, and targeted recommendations were proposed based on different levels of visual complexity. [ABSTRACT FROM AUTHOR]

Recent studies on the imitation of intransitive gestures suggest that the body part effect relies mainly upon the direct route of the dual-route model through a visuo-transformation mechanism. Here, we test the visuo-constructive hypothesis which posits that the visual complexity may directly potentiate the body part effect for meaningless gestures. We predicted that the difference between imitation of hand and finger gestures would increase with the visuo-spatial complexity of gestures. Second, we aimed to identify some of the visuo-spatial predictors of meaningless finger imitation skills. Thirty-eight participants underwent an imitation task containing three distinct set of gestures, that is, meaningful gestures, meaningless gestures with low visual complexity, and meaningless gestures with higher visual complexity than the first set of meaningless gestures. Our results were in general agreement with the visuo-constructive hypothesis, showing an increase in the difference between hand and finger gestures, but only for meaningless gestures with higher visuo-spatial complexity. Regression analyses confirm that imitation accuracy decreases with resource-demanding visuo-spatial factors. Taken together, our results suggest that the body part effect is highly dependent on the visuo-spatial characteristics of the gestures. [ABSTRACT FROM AUTHOR]

Objective: To investigate how the visual complexity of head-up displays (HUDs) influence the allocation of driver's attention in two separate visual domains (near and far domains). Background: The types and amount of information displayed on automobile HUDs have increased. With limited human attention capacity, increased visual complexity in the near domain may lead to interference in the effective processing of information in the far domain. Method: Near-domain and far-domain vision were separately tested using a dual-task paradigm. In a simulated road environment, 62 participants were to control the speed of the vehicle (SMT; near domain) and manually respond to probes (PDT; far domain) simultaneously. Five HUD complexity levels including a HUD-absent condition were presented block-wise. Results: Near domain performance was not modulated by the HUD complexity levels. However, the far domain detection accuracies were impaired as the HUD complexity level increased, with greater accuracy differences observed between central and peripheral probes. Conclusion: Increased HUD visual complexity leads to a biased deployment of driver attention toward the central visual field. Therefore, the formulation of HUD designs must be preceded by an in-depth investigation of the dynamics of human cognition. Application: To ensure driving safety, HUD designs should be rendered with minimal visual complexity by incorporating only essential information relevant to driving and removing driving-irrelevant or additional visual details. [ABSTRACT FROM AUTHOR]

This study delves into the complex dynamics of consumer attitudes toward sustainable products, particularly within the fast-moving consumer goods category, highlighting the significant correlation between elegant and minimalist design aesthetics and the establishment of green trust in sustainable product offerings. Interestingly, while visually complex packaging may capture visual attention, it does not generate higher levels of green trust compared to simpler alternatives within the same product category. The findings underscore the importance of simple packaging design in mitigating consumer skepticism toward manipulative intentions and enhancing trust in sustainable products. Furthermore, this research reveals that individuals with higher levels of expertise possess deeper insights in perceiving complexity as a potential form of manipulation, thereby exacerbating skepticism toward sustainable products. In summary, the research outcomes guide sustainable product packaging design, emphasizing alternative solutions to convoluted designs that may lead to confusion. The effectiveness of simple design expression in sustainable products is emphasized, fostering the transition toward sustainable business efficacy and long-term development. [ABSTRACT FROM AUTHOR]

Introduction: User experience is a higher-order construct than user interface. Nielsen's 1994 checklist, comprising ten factors including aesthetics, has endured for three decades. However, the precise dimensions of beauty within the web Porpose: environment remain elusive and inadequately defined. This study was designed to mitigate the aforementioned ambiguity. It aims to identify the aesthetic components of a single website based on Leibniz's theory and to rank these components according to the criteria's significance. A conceptual framework for the 'aesthetics of a single website' is proposed. Methodology: This study employed a systematic review methodology incorporating metasynthesis and Shannon's qualitative content analysis approach. A targeted keyword search was executed across six databases: Google Scholar, Emerald, Web of Science, IRANDOC, ISC, and SID. An initial pool of 1110 sources was identified. Subsequently, 64 documents were selected for the meta-synthesis study in accordance with the PRISMA statement. Leibniz's aesthetic theory underpins the qualitative coding framework for this study. The aesthetic factors delineated by Lavie and Tractinsky and the website analysis conducted by Guo and Hall served as foundational references for code development. Subsequently, an importance coefficient was computed for each identified aesthetic code, employing Shannon's qualitative content analysis method as outlined by Azar (2000). The aforementioned method conceptualizes each code within the source data as an exchanged communication. The sources themselves comprise the interviewees or experts who provided responses to the research query. Findings: A meta-synthesis yielded two categories, four concepts, and seventy-five aesthetic codes. The primary categories of website beauty were identified as the overarching levels of "objective aesthetics" and "subjective aesthetics." The subjective level pertains to the user and their perception (subject), while the objective level relates to the website design (object). Two primary concepts emerged within each category: semantic aesthetics and classical aesthetics. Within the objective aesthetics category, the codes of "typography" and "order" were deemed most important under the concept of classical aesthetics. Within the domain of subjective aesthetics, the principles of "attractive color combination," "intuitive navigation," and "moderate visual complexity," derived from classical aesthetic theory, were determined to be of paramount importance. A total of forty-three aesthetic codes for websites were identified as possessing a non-zero importance coefficient. Forty-three codes with a non-zero importance coefficient were identified and ranked from one to sixteen. The remaining thirtytwo codes, from a total of seventy-five, exhibited a zero Shannon entropy significance coefficient (indicating a single repetition in previous studies) and were consequently assigned to the seventeenth rank of Shannon's significance. The top twelve codes, prioritized as follows, were: observance of typography techniques in website content design, orderliness and cleanliness of website content, observance of symmetry in website content design, nonvisual complexity, and attractive website color combination. From the perspective of the website user's mind, "Coherence in website content design", "Intuitive website content navigation", "Adherence to organizational structure, sequence, and hierarchy in website design", "Optimal complexity for the website user", "Evoking a sense of richness and diversity for the website user", "Diverse website content design", "Visual appeal and engagement for the website user". Adherence to the Gestalt principle and the golden ratio in website design are among the other codes identified. Conclusion: Website administrators should consider both objective and subjective aesthetic factors to optimize user experience. While various studies have explored website aesthetics, this research is unique in its application of meta-synthesis and Shannon's entropy coding, constituting a pioneering effort both domestically (Iran) and internationally. Interdisciplinary collaboration between computer science and social science is recommended for advancing this field. [ABSTRACT FROM AUTHOR]

The current study investigates the influence of visual complexity and color harmony, two important aspects of visual esthetics in the online context, on customer engagement and word-of-mouth (WOM) transmission. We further examine whether consumer expectations and self-concept congruence operate as critical boundary conditions for the effect of these esthetic factors. The study uses an experimental design in which 402 respondents viewed researcher manipulated Instagram brand pages with varying levels of visual complexity and color combinations. The results show that independently, high levels of visual complexity, and complementary color combinations evoked greater consumer engagement and positive WOM intentions. Engagement levels declined when analogous color combinations were used on Instagram pages with high visual complexity and complementary colors on low visual complexity pages. Additionally, consumer engagement mediated the relationship between the visual esthetic elements and WOM transmission. Consumer expectations emerged as an important moderator of the effect of visual complexity on engagement but our prediction regarding the moderating effect of self-concept congruence was not supported. The results of this study contribute to a deeper understanding of the underlying process by which visual esthetic elements on image-centric platforms, like Instagram, interact to influence customer engagement and WOM. [ABSTRACT FROM AUTHOR]

Complexity has been known as a crucial psychological factor influencing the evaluation of the building facades preferences. However, little is known about the role of physical attributes of preferred building facades on perceived visual complexity. The objective of this study is to assess perceived visual complexity of urban building facades in terms of physical attribute in different levels. Discrete choice experiments were used to study the perceived visual complexity of preferred building facades. A sample of 213 students from Golestan University evaluated preference and perceived visual complexity of 36 pairs of images based on ten physical attributes of building facades in different levels (material (brick, stone), the contrast of materials (absent, present), color (absent, present), ornament (high, low), curve (straight, curved), vegetation (plants, no plants), windows orientations (vertical, horizontal), fenestration (large, small), articulation (side recesses, flat) and architectural style (modern, classic, traditional). The results revealed that all physical attributes of preferred building facades were found significant on perceived visual complexity expect for three attributes: architectural style, color and window to wall size. Thus, participant preferred a high-ornament facade with curved lines, vegetation, classical style, articulation, contrast between materials, as well as vertical windows. The articulation and ornament attributes were the most significant on perceived visual complexity. The results of this study can help city planners, architects, and designers to design facades with more general preferences and reduce the visual pollution of the cities. [ABSTRACT FROM AUTHOR]

Recently, deep learning-based methods for quality assessment of omnidirectional images (OIs) have gained widespread attention. However, existing methods face challenges because most omnidirectional image quality assessment (OIQA) methods inadequately consider projection distortions and visual complexity. In response, a multiscale feature aggregation convolutional neural network is proposed for OIQA to explore the feasibility of using multiscale features to strengthen the perception of projection distortion information. Specifically, cubemap projection (CMP) is employed to generate viewport images from equirectangular projection (ERP) images to effectively preserve more omnidirectional information. Subsequently, a multiscale feature extraction (MFE) module is designed to extract features at different levels and enhance the representation of distortion information. Additionally, a feature aggregation (FA) module is introduced to fuse multiscale features and fully improve the interconnection capability of the network. Finally, a quality regression (QR) module is employed to map the features to a quality score. Extensive experiments demonstrate the effectiveness and superiority of the proposed network over other state-of-the-art methods for accurately assessing OI quality. [ABSTRACT FROM AUTHOR]

Molecular visualization is a powerful way to represent the complex structure of molecules and their higher order assemblies, as well as the dynamics of their interactions. Although conventions for depicting static molecular structures and complexes are now well established and guide the viewer’s attention to specific aspects of structure and function, little attention and design classification has been devoted to how molecular motion is depicted. As we continue to probe and discover how molecules move - including their internal flexibility, conformational changes and dynamic associations with binding partners and environments - we are faced with difficult design challenges that are relevant to molecular visualizations both for the scientific community and students of cell and molecular biology. To facilitate these design decisions, we have identified twelve molecular animation design principles that are important to consider when creating molecular animations. Many of these principles pertain to misconceptions that students have primarily regarding the agency of molecules, while others are derived from visual treatments frequently observed in molecular animations that may promote misconceptions. For each principle, we have created a pair of molecular animations that exemplify the principle by depicting the same content in the presence and absence of that design approach. Although not intended to be prescriptive, we hope this set of design principles can be used by the scientific, education, and scientific visualization communities to facilitate and improve the pedagogical effectiveness of molecular animation.

Zhang Daqian (1899-1983) is an extremely influential painter in the history of modern Chinese painting. Among his works, the lotus paintings hold a special place in Zhang Daqian’s artistic career. This paper conducts a comparative study of Zhang Daqian’s early and late lotus paintings through quantitative analysis on three levels. Firstly, from the perspective of ink color, a quantitative comparative analysis concludes that the early works are characterized by high brightness, low contrast, and negative skewness. This indicates that the paintings possess a soft, delicate, and bright visual effect, giving a fresh and tranquil feeling. In contrast, the late works are characterized by low brightness, high contrast, and zero skewness, presenting a strong contrast, vivid colors, and visual balance. The color distribution in the late paintings is relatively balanced, forming a stark contrast to the soft style of the early works. Secondly, from the level of visual complexity, it is concluded that the early works have unique texture characteristics, while the late works are more uniform, consistent, and regular in these aspects, with stronger color contrast and dynamics, and more boldness. Finally, by extracting specific elements of “flowers, stems, leaves” for texture strokes and ink color gradation analysis, applying data quantification-based feature extraction and capturing important data information in MATLAB for data comparison, combined with professional analysis and research on related indicators of the artwork, the comparative results of quantitative analysis of Zhang Daqian’s early and late lotus paintings are given, summarizing the quantitative analysis results in descriptive language. The experimental results show that the algorithm has good performance, providing a solid basis for the quantitative analysis and comparative study of Zhang Daqian’s lotus paintings from early and late periods, and objectively presenting the style changes from “following the ancient” to “transforming the ancient” in Zhang Daqian’s lotus paintings through data.

Visual complexity is a crucial criterion for evaluating the quality of urban environments and a key dimension in arousal theory and visual preference theory. Objectively quantifying visual complexity holds significant importance for decision-making support in urban planning. This study proposes a visual complexity quantification model based on a support vector machine (SVM), incorporating six key indicators, to establish a mapping relationship between objective image features and subjective complexity perception. This model can efficiently and scientifically predict street view complexity on a large scale. The research findings include the following: (1) the introduction of a new quantification dimension for the urban environment complexity—hierarchical complexity– which reflects the richness of street elements based on an in-depth semantic understanding of images; (2) the established complexity quantification model demonstrates high accuracy, with the indicators ranked by contribution for compression ratio, grayscale contrast, hierarchical complexity, fractal dimension, color complexity, and symmetry; and (3) the model was applied to predict and analyze the visual complexity of the Xiaobailou and Wudadao Districts in Tianjin, revealing that the visual complexity of most streets is moderate, and targeted recommendations were proposed based on different levels of visual complexity.

Although it is well established that the visual complexity of a written word can influence processing, it is far less clear from a cross-script perspective, whether the overall visual complexity of the entire written lexicon also affects word recognition. This question can be answered with the data in megastudy of lexical decision in Chinese (MELD-CH), which was developed with over 800 participants responding to 12,587 simplified and traditional Chinese words. The results showed that lexical decision was slower but more accurate in simplified Chinese, which has about 22.5% less strokes, than traditional Chinese. This pattern could not be explained by a speed–accuracy trade-off. Moderate correlations were found in response times and error rates between the two scripts, indicating considerable overlap in processing despite the script difference. In addition, (generalised) linear mixed-effects modelling was used to examine whether the simplified and traditional Chinese groups differed in sensitivity towards linguistic variables. The results showed that the effects of word frequency, word length, and number of strokes were stronger in recognising simplified Chinese words, whereas the effects of number of words formed and number of meanings of the constituent characters were stronger in traditional Chinese. These results suggested that the visual-perceptual processing demands of simplified Chinese might force readers to focus more on local properties of the words, making them less sensitive to global properties that are defined over the entire lexicon. Finally, limitations and alternative explanations of the results were discussed. [ABSTRACT FROM AUTHOR]

Understanding visual complexity of urban environments may improve urban design strategies and limit visual pollution due to advertising, road signage, telecommunication systems and machinery. This paper aims at quantifying visual complexity specifically in urban streetscapes, by submitting a collection of geo-referenced photographs to a group of more than 450 internet users. The average complexity ranking issued from this survey was compared with a set of computer vision predictions, attempting to find the optimal match. Overall, a computer vision indicator matching comprehensively the survey outcome did not clearly emerge from the analysis, but a set of perceptual hypotheses demonstrated that some categories of stimuli are more relevant. The results show how images with contrasting colour regions and sharp edges are more prone to drive the feeling of high complexity. [ABSTRACT FROM AUTHOR]

Design plays a major role in online advertising. While specific aspects such as color or animation have been extensively studied, there is a surprising lack of comprehensive research on the overall impact of visual design and aesthetics. This study delved into the effects of varying levels of visual complexity in banner ads using the eye-tracking method. Out of 108 participants browsing test webpages with specially designed banners, data from 90 adequately measured data sets were used in the study. Notably, ads with a low level of visual complexity outperformed ads with a high level of visual complexity. While users noticed complex ads slightly faster (by 0.84%), they fixated on them significantly less (by 9.09%) and looked at them less frequently (by 4.79%). An implemented survey questionnaire examining the user perception of the banners reinforced the superiority of simple ads, as they were perceived as 4.40% more appealing in comparison. The study further delved into the correlation between objectively and subjectively evaluated data, exploring the credibility of subjective methods in the process. Considering our results and findings from other studies, it was evident that visually complex ads demanded more cognitive effort, could be more distracting, negatively impacted attention, could contribute to banner blindness and were perceived as less appealing. [ABSTRACT FROM AUTHOR]

In drug-resistant epilepsy, a visual inspection of intracranial electroencephalography (iEEG) signals is often needed to localize the epileptogenic zone (EZ) and guide neurosurgery. The visual assessment of iEEG time-frequency (TF) images is an alternative to signal inspection, but subtle variations may escape the human eye. Here, we propose a deep learning-based metric of visual complexity to interpret TF images extracted from iEEG data and aim to assess its ability to identify the EZ in the brain. We analyzed interictal iEEG data from 1928 contacts recorded from 20 children with drug-resistant epilepsy who became seizure-free after neurosurgery. We localized each iEEG contact in the MRI, created TF images (1–70 Hz) for each contact, and used a pre-trained VGG16 network to measure their visual complexity by extracting unsupervised activation energy (UAE) from 13 convolutional layers. We identified points of interest in the brain using the UAE values via patient- and layer-specific thresholds (based on extreme value distribution) and using a support vector machine classifier. Results show that contacts inside the seizure onset zone exhibit lower UAE than outside, with larger differences in deep layers (L10, L12, and L13: p < 0.001). Furthermore, the points of interest identified using the support vector machine, localized the EZ with 7 mm accuracy. In conclusion, we presented a pre-surgical computerized tool that facilitates the EZ localization in the patient's MRI without requiring long-term iEEG inspection. [ABSTRACT FROM AUTHOR]

Cluster separation is required to perform multi-class visual statistics tasks and plays an essential role in information processing in visualization. This cognition behavioral study investigated the cluster separation task and the effects of visual complexity and task difficulty. A total of 32 college students (18 men and 14 women, with ages ranging from 18 to 25 years; mean = 21.2, SD = 3.9) participated in this study. The observers' average response accuracy, reaction time, mental effort, and comprehensive cognitive efficiency were measured as functions of three levels of visual complexity and task difficulty. The levels of visual complexity and task difficulty were quantified via an optimized complexity evaluation method and discrimination judgment task, respectively. The results showed that visual complexity and task difficulty significantly influenced comprehensive cognitive efficiency. Moreover, a strong interaction was observed between the effects of visual complexity and task difficulty. However, there was no positive linear relationship between the mental effort and the complexity level. Furthermore, two-dimensional color × shape redundant coding showed higher cognitive efficiency at low task difficulty levels. In contrast, the one-dimensional color encoding approach showed higher cognitive efficiency at increased task difficulty levels. The findings of this study provide valuable insights into designing more efficient and user-friendly visualization in the future. [ABSTRACT FROM AUTHOR]

Advanced driver assistance systems (ADAS) need to account for the driver's awareness of the environment to be effectively used. This study examines the impact of environmental features (eg, visual complexity, object density, roadway type, lighting) on drivers' situation awareness (SA). This is achieved using a controlled study with 40 participants. Using a split-plot design, the participants were shown 30 out of 75 real-world driving scenarios displayed in a driving simulator environment. Participants' responses to Situational Awareness Global Assessment Technique (SAGAT) queries on the type and coordinates of objects in the scene were used to calculate SA scores. A hurdle model was developed to estimate participants' SA scores. The key findings highlight visual complexity as a significant predictor of SA scores. This predictor was easy to compute and able to capture the complexity of objects that impact road safety as well as the visual clutter in the background. The model showed that drivers were able to identify at least one object of interest in complex environments with high visual complexity and with many objects. A higher proportion of vulnerable road users was associated with a greater likelihood of a non-zero SA score, but the SA score was lower compared to environments with higher proportions of cars. The findings of this study provide insights into the environmental factors to be considered for SA predictive models. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer-Aided Design & Computer Graphics / Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Raven matrices are widely considered a pure test of cognitive abilities. Previous research has examined the extent to which cognitive strategies are predictive of the number of correct responses to Raven items. This study examined whether response times can be explained directly from the centrality and visual complexity of the matrix cells (edge density and perceived complexity). A total of 159 participants completed a 12-item version of the Raven Advanced Progressive Matrices. In addition to item number (an index of item difficulty), the findings demonstrated a positive correlation between the visual complexity of Raven items and both the mean response time and the number of fixations on the matrix (a strong correlate of response time). Moreover, more centrally placed cells as well as more complex cells received more fixations. It is concluded that response times on Raven matrices are impacted by low-level stimulus attributes, namely, visual complexity and eccentricity. [ABSTRACT FROM AUTHOR]

Origin–destination (OD) visualizations can help to understand movement data. Unfortunately, they are often cluttered due to the quadratic growth of the data and complex depictions of the multiple dimensions in the data. Many domain experts have designed visualizations to reduce visual complexity and display multiple data variables. However, OD visualizations have not been well classified, which makes it hard to employ such methods for reducing the visual complexity systematically. In this article, we propose a novel classification scheme for static OD visualizations that considers five aspects: the granularity of flows, the dimensionality in and of the display space, the semantics of the display space, the representation of nodes and flows, and the ways of relating two visualizations. We evaluate the proposed classification scheme using published visualization examples and show that it is effective and expressive. [ABSTRACT FROM AUTHOR]

Tangram pictures are abstract pictures which may be used as stimuli in various fields of experimental psychology and are often used in the field of dialogue psychology. The present study provides the first norms for a set of 332 tangram pictures. These pictures were standardized on a set of variables classically used in the literature on cognitive processes, such as visual perception, language, and memory: name agreement, image agreement, familiarity, visual complexity, image variability, and age of acquisition. Furthermore, norms for concreteness were also provided owing to the influence of this variable on the processes involved in lexical production. Correlational analyses on all variables were performed on the data collected from French native speakers. This new set of standardized pictures constitutes a reliable database for researchers when they select tangram pictures. Given the abstract nature of tangram pictures, this paper also discusses the similarities and differences with the literature on line drawings, and highlights their value for dialogue psychology studies, for psycholinguistics studies, and for cognitive psychology in general. [ABSTRACT FROM AUTHOR]

This article presents subjective norms for 1031 emojis in six dimensions: visual complexity, familiarity, frequency of use, clarity, emotional valence, and emotional arousal. This is the largest normative study conducted so far that relies on subjective ratings. Unlike the few existing normative studies, which mainly comprise face emojis, here we present a wide range of emoji categories. We also examine the correlations between the dimensions assessed. Our results show that, in terms of their affective properties, emojis are analogous to other stimuli, such as words, showing the expected U-shaped relationship between valence and arousal. The relationship between affective properties and other dimensions (e.g., between valence and familiarity) is also similar to the relationship observed in words, in the sense that positively valenced emojis are more familiar than negative ones. These findings suggest that emojis are suitable stimuli for studying affective processing. Emoji-SP will be highly valuable for researchers of various fields interested in emojis, including computer science, communication, linguistics, and psychology. The full set of norms is available at: https://osf.io/dtfjv/. [ABSTRACT FROM AUTHOR]

Copyright of Estudios Pedagogicos (Valdivia) is the property of Estudios Pedagogicos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this article, I study the stylistic features of Japanese cinematography of the middle of the twentieth century, which was introduced to European critics and the general public in the 1950s. The cinematic style of the analyzed Japanese films is associated with the concept of visual complexity, borrowed from Le Fanu’s book Mizoguchi and Japan (Le Fanu, 2018). One of the manifestations of visual complexity in the films of Kenji Mizoguchi, YasujiroOzu, early Akira Kurosawa and other Japanese film directors of the ’50s, is that the viewer, experiencing anxiety and disharmony, is forced to build up in his mind an image, that is difficult to identify in the first moments of its screen existence, to regognizable objectivity. Another interesting aspect of visual complexity is the motionless long shots taken by a camera distanced from the object of observation—seemingly impassive, but at the same time bringing the viewer to a high degree of tension. These manifestations of visual complexity in Japanese cinema are compared to the outwardly similar forms created in the same period or somewhat later by such European film modernists and representatives of the American New Hollywood as Ingmar Bergman, Michelangelo Antonioni, Andrei Tarkovsky, Stanley Kubrick and, mainly, Robert Bresson. However, analyzing primarily Kenji Mizoguchi’s Ugetsu Monogatari (“Tales of Moonlight and Rain”) and relying on the article A Lesson in Japanese Film Style by André Bazin and works by Jean-Luc Godard, Mark Le Fanu and Jean-Marie Gustave Le Clézio, I show that, in Bazin’s words, Japanese films do not so much give a sense of the style of the work that characterizes their authors as they express the anonymous “artistic spirit of a distinct civilization” (as cited in Le Fanu, 2018, p. 179). This means that Japanese cinema of the period under study contains artistic traditions that were formed and developed long before the birth of cinema to a much more pronounced degree than European and American auteur cinema. In particular, Japanese cinematography is obviously influenced by theatrical traditions, primarily Noh, the ancient traditions of making folding screens, tapestries, and erotic miniatures. All this, in turn, is a part of Japanese mentality rather than of Japanese intellectual culture. And this largely distinguishes Japanese cinema from formally similar European and American film modernism, predetermined not so much by mental factors and old cultural traditions as by contemporary intellectual discourses, primarily existentialist and Christian-personalist philosophy. В статье рассматриваются стилистические особенности японского кинематографа середины прошлого столетия, знакомство с которым европейских критиков и широкой публики происходило в 1950-е годы. Анализируемый автором кинематографический стиль японских фильмов связывается с понятием «визуальная сложность», позаимствованным из книги Марка Ле Фаню «Мидзогути и Япония» (Ле Фаню, 2018). Одно из рассматриваемых в статье проявлений «визуальной сложности» в картинах К. Мидзогути, Я. Одзу, раннего А. Куросавы и других японских кинорежиссеров 50-х заключается в том, что зритель, испытывающий при этом беспокойство и дисгармонию, вынужден достраивать в воображении до идентифицируемой предметности трудно опознаваемое в первые моменты своего экранного существования изображение. Другой интересующий автора момент «визуальной сложности» — снятые кинокамерой, достаточно далеко отстоящей от объекта наблюдения, неподвижные длинные планы, казалось бы, бесстрастные, но в то же время доводящие зрителя до высокой степени напряжения. Эти проявления «визуальной сложности» в японском кино сопоставляются с внешне похожими на них формами созданных в этот же период или несколько позже фильмов таких европейских киномодернистов и представителей американского Нового Голливуда, как И. Бергман, М. Антониони, А. Тарковский, С. Кубрик и, главным образом, Р. Брессон. Однако, анализируя прежде всего картину Кэндзи Мидзогути «Угэцу моногатари» («Сказки туманной луны после дождя») и опираясь в своем анализе и обобщениях на статью А. Базена «Урок японского киностиля» и на тексты Ж.-Л. Годара, М. Ле Фаню и М. Г. Леклезио, автор показывает, что, говоря словами Базена, японские фильмы не столько дают почувствовать стиль произведения, характеризующий их авторов, сколько выражают анонимный «художественный дух отдельной цивилизации» (цит. по: Ле Фаню, с. 179). Это означает, что японское кино исследуемого периода содержит в себе формировавшиеся и развивавшиеся задолго до рождения кинематографа художественные традиции в гораздо более выраженной степени, чем европейское и американское «авторское кино». В частности, выявляется очевидное влияние на японский кинематограф театральной традиции прежде всего театра Но, старинных традиций изготовления ширм, гобеленов и эротической миниатюры. В свою очередь, все эти традиции причастны не столько к японской интеллектуальной культуре, сколько к японской ментальности. И это в значительной степени отличает японский кинематограф от формально похожего на него европейского и американского киномодернизма, предопределенного не столько ментальными факторами и старыми культурными традициями, сколько современными ему интеллектуальными дискурсами прежде всего экзистенциалистской и христианско-персоналистской философией.

Previous research has shown that the perceived visual complexity of an image is correlated with understandability of the image. It was considered that prior knowledge of the contents of an image makes images easier to understand, and thus reduces perceived visual complexity. In the present study, we examined the effect of prior knowledge on perceived visual complexity of texture images. We designed an experiment in which participants observed and rated four texture images with different levels of complexity and understandability; one group of participants received prior knowledge in the form of verbal cues about the names of the target stimuli while the other group did not receive any information regarding image content. We found that the effect of prior knowledge on visual complexity perception varied for the different images. For an image with low initial complexity, if cued information about the image is three-dimensional or dynamic, prior knowledge does not decrease but instead increases the perceived visual complexity. Moreover, cues that increase perceived visual complexity can be verbal rather than visual cues.

In this study, we examined the effects of spatial attention in Hangul word recognition depending on visual factors. The visual complexity of words (Experiment 1) and contrast (Experiment 2) were manipulated to examine whether the effect of spatial attention differs depending on visual quality. Participants responded to words with and without codas in experiment 1 and words in high-contrast and low-contrast conditions in experiment 2. The effects of spatial attention were investigated by calculating the difference in performance between the condition where spatial cues were given at the target location (valid trial) and the condition where the spatial cues were not given at the target location (invalid trial) as the cuing effects. As a result, the cuing effects were similar depending on the complexity of the words. It indicates that the effects of spatial attention were not different across the visual complexity conditions. The cuing effects were greater in the low-contrast condition than in the high-contrast condition. The greater effect of spatial attention when the contrast is low was explained as a mechanism of signal enhancement. [ABSTRACT FROM AUTHOR]

Training data for user behavior models that predict subjective dimensions of visual perception are often too scarce for deep learning methods to be applicable. With the typical datasets in HCI limited to thousands or even hundreds of records, feature-based approaches are still widely used in visual analysis of graphical user interfaces (UIs). In our paper, we benchmarked the predictive accuracy of the two types of neural network (NN) models, and explored the effects of the number of features, and the dataset volume. To this end, we used two datasets that comprised over 4000 webpage screenshots, assessed by 233 subjects per the subjective dimensions of Complexity, Aesthetics and Orderliness. With the experimental data, we constructed and trained 1908 models. The feature-based NNs demonstrated 16.2%-better mean squared error (MSE) than the convolutional NNs (a modified GoogLeNet architecture); however, the CNNs' accuracy improved with the larger dataset volume, whereas the ANNs' did not: therefore, provided that the effect of more data on the models' error improvement is linear, the CNNs should become superior at dataset sizes over 3000 UIs. Unexpectedly, adding more features to the NN models caused the MSE to somehow increase by 1.23%: although the difference was not significant, this confirmed the importance of careful feature engineering. [ABSTRACT FROM AUTHOR]

Chinese ice-ray lattices are perhaps one of the earliest and controlled designs of asymmetric and complex patterns applied as a traditional motif in windows. Such intricate and complex designs developed centuries back have created an evident curiosity to explore its underlying geometric rules. Some scholars used the Shape Grammar as a tool to explain and recreate similar patterns. The previous studies conceive the ice-ray lattice design as the iterative subdivisions of a polygon. However, they missed explaining this geometric quality through the discussion of fractal geometry, which can explain the shapes consuming self-similar or self-affine repetitions of itself at different scales. As a novel approach, this paper analytically focuses on the fractal characters of ice-ray lattice designs and uses fractal geometry as a unique tool for generating different types of ice-ray lattices. The significance of this study is the demonstration of the efficacy of fractal geometry and the simple geometric rule of IFS for analyzing and algorithmically modeling complex lattices and cracked-like patterns.

In drug-resistant epilepsy, a visual inspection of intracranial electroencephalography (iEEG) signals is often needed to localize the epileptogenic zone (EZ) and guide neurosurgery. The visual assessment of iEEG time-frequency (TF) images is an alternative to signal inspection, but subtle variations may escape the human eye. Here, we propose a deep learning-based metric of visual complexity to interpret TF images extracted from iEEG data and aim to assess its ability to identify the EZ in the brain. We analyzed interictal iEEG data from 1928 contacts recorded from 20 children with drug-resistant epilepsy who became seizure-free after neurosurgery. We localized each iEEG contact in the MRI, created TF images (1–70 Hz) for each contact, and used a pre-trained VGG16 network to measure their visual complexity by extracting unsupervised activation energy (UAE) from 13 convolutional layers. We identified points of interest in the brain using the UAE values via patient- and layer-specific thresholds (based on extreme value distribution) and using a support vector machine classifier. Results show that contacts inside the seizure onset zone exhibit lower UAE than outside, with larger differences in deep layers (L10, L12, and L13: p < 0.001). Furthermore, the points of interest identified using the support vector machine, localized the EZ with 7 mm accuracy. In conclusion, we presented a pre-surgical computerized tool that facilitates the EZ localization in the patient’s MRI without requiring long-term iEEG inspection.

Design plays a major role in online advertising. While specific aspects such as color or animation have been extensively studied, there is a surprising lack of comprehensive research on the overall impact of visual design and aesthetics. This study delved into the effects of varying levels of visual complexity in banner ads using the eye-tracking method. Out of 108 participants browsing test webpages with specially designed banners, data from 90 adequately measured data sets were used in the study. Notably, ads with a low level of visual complexity outperformed ads with a high level of visual complexity. While users noticed complex ads slightly faster (by 0.84%), they fixated on them significantly less (by 9.09%) and looked at them less frequently (by 4.79%). An implemented survey questionnaire examining the user perception of the banners reinforced the superiority of simple ads, as they were perceived as 4.40% more appealing in comparison. The study further delved into the correlation between objectively and subjectively evaluated data, exploring the credibility of subjective methods in the process. Considering our results and findings from other studies, it was evident that visually complex ads demanded more cognitive effort, could be more distracting, negatively impacted attention, could contribute to banner blindness and were perceived as less appealing.

Cluster separation is required to perform multi-class visual statistics tasks and plays an essential role in information processing in visualization. This cognition behavioral study investigated the cluster separation task and the effects of visual complexity and task difficulty. A total of 32 college students (18 men and 14 women, with ages ranging from 18 to 25 years; mean = 21.2, SD = 3.9) participated in this study. The observers’ average response accuracy, reaction time, mental effort, and comprehensive cognitive efficiency were measured as functions of three levels of visual complexity and task difficulty. The levels of visual complexity and task difficulty were quantified via an optimized complexity evaluation method and discrimination judgment task, respectively. The results showed that visual complexity and task difficulty significantly influenced comprehensive cognitive efficiency. Moreover, a strong interaction was observed between the effects of visual complexity and task difficulty. However, there was no positive linear relationship between the mental effort and the complexity level. Furthermore, two-dimensional color × shape redundant coding showed higher cognitive efficiency at low task difficulty levels. In contrast, the one-dimensional color encoding approach showed higher cognitive efficiency at increased task difficulty levels. The findings of this study provide valuable insights into designing more efficient and user-friendly visualization in the future.

This research introduces the concept of ‘digital claustrophobia,’ examining how stable individual differences in claustrophobic tendencies can generate affective reactions to spatial elements online. The findings indicate that elevated claustrophobic tendencies lead to emotional discomfort and negatively moderate spatial constraint effects on website evaluations and anticipated product satisfaction. A series of exploratory studies establishes that (1) a common measure of individual differences in claustrophobia applies in digital commerce contexts, (2) claustrophobia alters reactions to spatial constraints, which changes downstream consequences such as mood, website design evaluation, and anticipated product satisfaction, and (3) these effects persist for more claustrophobic individuals in spatially constrained digital interfaces even when general affective measures such as mood are explicitly primed. This work is the first to investigate the role of claustrophobic tendencies in e-commerce environments in the context of anticipated satisfaction and suggests a foundation for numerous future research avenues.

Complex systems have become a popular lens for analyzing cities and complexity theory has many implications for urban performance and resilience. This paper develops a typology of measures and indicators for assessing the physical complexity of the built environment at the scale of urban design. It extends quantitative measures from city planning, network science, ecosystems studies, fractal geometry, statistical physics, and information theory to the analysis of urban form and qualitative human experience. Metrics at multiple scales are scattered throughout diverse bodies of literature and have useful applications in analyzing the adaptive complexity that both evolves and results from local design processes. In turn, they enable urban designers to assess resilience, adaptability, connectedness, and livability with an advanced toolkit. The typology developed here applies to empirical research of various neighborhood types and design standards. It includes temporal, visual, spatial, scaling, and connectivity measures of the urban form. Today, prominent urban design movements openly embrace complexity but must move beyond inspiration and metaphor to formalize what "complexity" is and how we can use it to assess both the world as-is as well as proposals for how it could be instead.

Aesthetic appeal of a visual image can influence performance in time-critical tasks, even if it is irrelevant to the task. This series of experiments examined whether aesthetic appeal can act as an object attribute that guides visual search. If appeal enhances the salience of the targets pre-attentively, then appealing icons would lead to more efficient searches than unappealing targets and, conversely, appeal of distractors would reduce search efficiency. Three experiments (N = 112) examined how aesthetic appeal influences performance in a classic visual search task. In each experiment, participants completed 320 visual search trials, with icons varying in rated aesthetic appeal and either visual complexity (Experiments 1 and 2) of concreteness (Experiment 3) among two, four, eight, or 11 distractor icons. While target appeal did not influence search efficiency it sped up search times in all three experiments: appealing targets led to faster response time (RT) than unappealing targets across all experiments, and compared to neutral distractors, appealing distractors slowed search RT down. These findings are the first to show that an object's aesthetic appeal influences visual search performance. [ABSTRACT FROM AUTHOR]

The visual complexity of interface plays a crucial role in user experience. Previous studies have extensively investigated website complexity, while the visual complexity of mobile applications gets seldom attention. This study explored the effect of interface complexity of mobile news apps on user search behaviors and satisfaction by dividing visual complexity into quantity complexity and layout complexity. Thirty-four subjects were invited to take part in the task-oriented eye-tracking experiment. The results revealed that a high level of quantity complexity increased users' revisit counts, fixation counts, and saccade counts. A high level of layout complexity increased users' revisit counts and saccade counts while fixation counts decreased first and then increased. Additionally, user satisfaction was negatively correlated with quantity complexity levels, while there was an inverted-U shape between user satisfaction and layout complexity levels. Understanding the effect of visual complexity of mobile news apps on user search behaviors and satisfaction would contribute to providing better guidelines for designers to develop mobile news products with an appropriate complexity layout and improve user satisfaction. [ABSTRACT FROM AUTHOR]

An emotion-induced memory trade-off effect is frequently reported when participants have to memorize complex items that include both neutral and emotional features. This bias corresponds to better remembering of central emotional information accompanied by poor performance related to neutral background information. Although the trade-off effect has been mainly associated with attentional bias toward emotional content, findings suggest that other non-attentional cognitive processes could also be involved. The aim of this work was to assess whether emotional effects would be reported apart from their influence on attentional processing in an immediate delay memory task. Three studies were conducted. In Study 1, manipulation of the diffusion quality of emotional content allowed us to select focal emotional pictures vs. diffuse emotional pictures, which prevented attentional focus. The two studies that followed consisted of a recognition task of low- and highcomplexity pictures in which we used partial visual cues during the test that could display either the emotional elements (i.e., central patch cues, Study 2) or the peripheral elements (i.e., peripheral patch cues, Study 3) of the focal emotional pictures. Results from Studies 2 and 3 replicated traditional tradeoff effects only for high-complexity pictures. In addition, diffuse emotional pictures were associated with lower memory performance than were neutral pictures, suggesting that emotion features could both disturb and enhance (via their attentional effect) encoding processes. [ABSTRACT FROM AUTHOR]

Word length and frequency are two of the "big three" factors that affect eye movements in natural reading. Although these factors have been extensively investigated, all previous studies manipulating word length have been confounded with changes in visual complexity (longer words have more letters and are more visually complex). We controlled stroke complexity across one-character (short) and two-character (long) high- and low-frequency Chinese words (to avoid complexity confounds) and recorded readers' eye movements during sentence reading. Both word length and frequency yielded strong main effects for fixation time measures. For saccadic targeting and skipping probability, word length effects, but not word frequency effects, occurred. Critically, the interaction was not significant regardless of stroke complexity, indicating that word length and frequency independently influence lexical identification and saccade target selection during Chinese reading. The results provide evidence for character-level representations during Chinese word recognition in natural reading., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.