Hasil untuk "Visual arts"

Carlos Navarro-Moral

Investigar sobre el proceso de creación es un reto que enfrenta el ámbito de la investigación basada en arte. Son pocas las investigaciones que se han dirigido a mostrar la complejidad que conlleva el proceso de creación artística. La investigación que se muestra a continuación es un ejemplo de cómo acercarse al mundo de la creación artística para analizarlo y comprenderlo. Para ello se ha llevado a cabo un estudio fenomenológico trascendental durante la elaboración de dos retratos de una joven llamada Irene. Se ha comenzado haciendo un análisis profundo de la identidad de Irene mediante el uso de entrevistas semiestructuradas; a continuación, se han elaborado diarios reflexivos que recogen los procesos fenomenológicos trascendentales asociados a la elaboración de los retratos de Irene. El valor de esta investigación reside en que sus resultados muestran específicamente el análisis llevado a cabo sobre el proceso de creación artística abriendo, en alguna medida, “la caja negra” que encierra la magia del proceso creativo.

Eduardo Miranda

This paper explains the Visual Milestone Planning (VMP) method using an agile vocabulary to facilitate its adoption by agile practitioners as a front end for a hybrid development process. VMP is a visual and collaborative planning approach which promotes a shared understanding of the work approach and commitment through the direct manipulation by team members of the reified planning constructs involved in the development of the plan. Once the product backlog has been established and relevant milestones identified, a novel construct called the milestone planning matrix is used to document the allocation of product backlog items to milestones. The milestones due dates are later determined by grouping sticky notes representing the work to be performed into time-boxes called work packages and accommodating them on a resource and time scaled scheduling canvas very much as it would be done in a Tetris game.

Adewale Christopher Oyewo, Azeez Akinwumi Sesan

The persistence of violence in Nigeria’s socio-political space has called for critical interventions of government and other stakeholders with a view to finding solutions from ideological and combative fronts. Nollywood filmmakers have been consistently intervening in national discourses aimed at ushering in peace and national cohesion through the subject matter and themes of their films. Pascal Amanfo’s Nation Under Siege (2013) is one of the Nollywood films that have intervened in ideological discourse aimed at sustainable peace in Nigeria. With the tenets of psychoanalysis, the article critiques the film’s focus on Boko Haram insurgents. With content analysis, the article found that the film highlights the operative strategies of the insurgents and the ineptitude of the government in the fight against them. The film, however, upholds the view that ideological warfare should also be engaged in the fight against the insurgents as underlined in the characterisation and role of Lina, a prostitute in the film. With the topicality and relevance of the film to ideological discourse, Nollywood has come of age considering the quality of its story and boldness to take risk in the face of state censorship.

Cristiana Bartolomei, Caterina Morganti

This paper offers a critical and original reading of Friedensreich Hundertwasser’s work, focusing on the continuity between his visual language in painting and architecture. Moving beyond symbolic or stylistic interpretations, the analysis introduces the concept of atmospheric drawing: a perceptual grammar in which color, line, and texture do not merely represent but generate multisensory and affective environments. Hundertwasser’s graphic signs –spirals, organic curves, chromatic contrasts– are interpreted as compositional devices that activate emotional responses and structure space, both pictorial and architectural. By comparing specific paintings such as Irinaland over the Balkans with buildings like the Hundertwasserhaus or the Waldspirale, the article demonstrates how drawing operates as a generative process that redefines the relationship between humans, architecture, and nature. The concept of the ‘third skin’ is reexamined as a sensory interface, mediating the boundaries between interiority and landscape. Finally, the paper proposes the idea of visual ecology as a framework for understanding drawing as a critical and environmental practice. In doing so, it positions Hundertwasser’s work as a living laboratory for rethinking the role of drawing, not as a static representation of reality, but as a creative tool for shaping how we perceive, inhabit, and imagine the world.

Xindi Wang, Alexander J. Gates, Magnus Resch et al.

From disparities in the number of exhibiting artists to auction opportunities, there is evidence of women's under-representation in visual art. Here we explore the exhibition history and auction sales of 65,768 contemporary artists in 20,389 institutions, revealing gender differences in the artist population, exhibitions and auctions. We distinguish between two criteria for gender equity: gender-neutrality, when artists have gender-independent access to exhibition opportunities, and gender-balanced, that strives for gender parity in representation, finding that 58\% of institutions are gender-neutral but only 24\% are gender-balanced, and that the fraction of man-overrepresented institutions increases with institutional prestige. We define artist's co-exhibition gender to capture the gender inequality of the institutions that an artist exhibits. Finally, we use logistic regression to predict an artist's access to the auction market, finding that co-exhibition gender has a stronger correlation with success than the artist's gender. These results help unveil and quantify the institutional forces that relate to the persistent gender imbalance in the art world.

Diederik Aerts, Jonito Aerts Arguëlles, Sandro Sozzo

We prove that the quantum measurement process contains the same warping mechanism that occurs in categorical perception, a phenomenon ubiquitous in human perception. This warping causes stimuli belonging to the same category to be perceived as more similar, while stimuli belonging to different categories are perceived as more different. As a result of a detailed study of the quantum measurement using the Bloch representation, we identify the natural metric for pure states, namely the Fubini Study metric, and the natural metric for density states, namely the trace class metric. The warping mechanism of categorical perception is then manifested, when the distances between pure states, playing the role of stimuli for the quantum measurement, are warped into the distances between density states, playing the role of percepts for quantum measurement. We work out the example of a two-dimensional quantum model, a qubit, with 'light' and 'dark' as the two eigenstates, and show how the typical contraction and dilation warping of human perception manifest themselves in this example of the quantum measurement model of light and dark.

Byung Hoon Lee, Wooseok Shin, Sung Won Han

The word-level lipreading approach typically employs a two-stage framework with separate frontend and backend architectures to model dynamic lip movements. Each component has been extensively studied, and in the backend architecture, temporal convolutional networks (TCNs) have been widely adopted in state-of-the-art methods. Recently, dense skip connections have been introduced in TCNs to mitigate the limited density of the receptive field, thereby improving the modeling of complex temporal representations. However, their performance remains constrained owing to potential information loss regarding the continuous nature of lip movements, caused by blind spots in the receptive field. To address this limitation, we propose TD3Net, a temporal densely connected multi-dilated convolutional network that combines dense skip connections and multi-dilated temporal convolutions as the backend architecture. TD3Net covers a wide and dense receptive field without blind spots by applying different dilation factors to skip-connected features. Experimental results on a word-level lipreading task using two large publicly available datasets, Lip Reading in the Wild (LRW) and LRW-1000, indicate that the proposed method achieves performance comparable to state-of-the-art methods. It achieved higher accuracy with fewer parameters and lower floating-point operations compared to existing TCN-based backend architectures. Moreover, visualization results suggest that our approach effectively utilizes diverse temporal features while preserving temporal continuity, presenting notable advantages in lipreading systems. The code is available at our GitHub repository (https://github.com/Leebh-kor/TD3Net).

Jing Zhang, Liang Zheng, Meng Wang et al.

This paper develops small vision language models to understand visual art, which, given an art work, aims to identify its emotion category and explain this prediction with natural language. While small models are computationally efficient, their capacity is much limited compared with large models. To break this trade-off, this paper builds a small emotional vision language model (SEVLM) by emotion modeling and input-output feature alignment. On the one hand, based on valence-arousal-dominance (VAD) knowledge annotated by psychology experts, we introduce and fuse emotional features derived through VAD dictionary and a VAD head to align VAD vectors of predicted emotion explanation and the ground truth. This allows the vision language model to better understand and generate emotional texts, compared with using traditional text embeddings alone. On the other hand, we design a contrastive head to pull close embeddings of the image, its emotion class, and explanation, which aligns model outputs and inputs. On two public affective explanation datasets, we show that the proposed techniques consistently improve the visual art understanding performance of baseline SEVLMs. Importantly, the proposed model can be trained and evaluated on a single RTX 2080 Ti while exhibiting very strong performance: it not only outperforms the state-of-the-art small models but is also competitive compared with LLaVA 7B after fine-tuning and GPT4(V). The code is available at https://github.com/BetterZH/SEVLM-code.

Sarah Alsufyani, Matthew Forshaw, Sara Johansson Fernstad

Missing data, the data value that is not recorded for a variable, occurs in almost all statistical analyses and may be caused by many reasons, such as lack of collection or a lack of documentation. Researchers need to adequately deal with this issue to provide a valid analysis. The visualization of missing values plays an important role in supporting the investigation and understanding of the missing data patterns. While some techniques and tools for visualization of missing values are available, it is still a challenge to select the right visualization that will fulfil the user requirements for visualizing missing data. This paper provides an overview and state-of-the-art report (STAR) of research literature focusing on missing values visualization. To the best of our knowledge, this is the first survey paper with a focus on missing data visualization. The goal of this paper is to encourage visualization researchers to increase their involvement with Missing data visualization.

Bereket A. Yilma, Luis A. Leiva

Visual art (VA) recommendation is complex, as it has to consider the interests of users (e.g. museum visitors) and other stakeholders (e.g. museum curators). We study how to effectively account for key stakeholders in VA recommendations while also considering user-centred measures such as novelty, serendipity, and diversity. We propose MOSAIC, a novel multimodal multistakeholder-aware approach using state-of-the-art CLIP and BLIP backbone architectures and two joint optimisation objectives: popularity and representative selection of paintings across different categories. We conducted an offline evaluation using preferences elicited from 213 users followed by a user study with 100 crowdworkers. We found a strong effect of popularity, which was positively perceived by users, and a minimal effect of representativeness. MOSAIC's impact extends beyond visitors, benefiting various art stakeholders. Its user-centric approach has broader applicability, offering advancements for content recommendation across domains that require considering multiple stakeholders.

Diederik Aerts, Jonito Aerts Arguēlles, Lester Beltran et al.

Identical systems, or entities, are indistinguishable in quantum mechanics (QM), and the symmetrization postulate rules the possible statistical distributions of a large number of identical quantum entities. However, a thorough analysis on the historical development of QM attributes the origin of quantum statistics, in particular, Bose-Einstein statistics, to a lack of statistical independence of the micro-states of identical quantum entities. We have recently identified Bose-Einstein statistics in the combination of words in large texts, as a consequence of the entanglement created by the meaning carried by words when they combine in human language. Relying on this investigation, we put forward the hypothesis that entanglement, hence the lack of statistical independence, is due to a mechanism of contextual updating, which provides deeper reasons for the appearance of Bose-Einstein statistics in human language. However, this investigation also contributes to a better understanding of the origin of quantum mechanical statistics in physics. Finally, we provide new insights into the intrinsically random behaviour of microscopic entities that is generally assumed within classical statistical mechanics.

Diederik Aerts, Jonito Aerts Arguëlles, Lester Beltran et al.

We present a theoretical and empirical investigation of the statistical behaviour of the words in a text produced by human language. To this aim, we analyse the word distribution of various texts of Italian language selected from a specific literary corpus. We firstly generalise a theoretical framework elaborated by ourselves to identify 'quantum mechanical statistics' in large-size texts. Then, we show that, in all analysed texts, words distribute according to 'Bose--Einstein statistics' and show significant deviations from 'Maxwell--Boltzmann statistics'. Next, we introduce an effect of 'word randomization' which instead indicates that the difference between the two statistical models is not as pronounced as in the original cases. These results confirm the empirical patterns obtained in texts of English language and strongly indicate that identical words tend to 'clump together' as a consequence of their meaning, which can be explained as an effect of 'quantum entanglement' produced through a phenomenon of 'contextual updating'. More, word randomization can be seen as the linguistic-conceptual equivalent of an increase of temperature which destroys 'coherence' and makes classical statistics prevail over quantum statistics. Some insights into the origin of quantum statistics in physics are finally provided.

H. Thuneberg, Hannu Salmi, F. Bogner

Abstract An informal mathematical module integrating Arts (modifying STEM to STEAM) and following an inquiry-based learning approach was applied to a sample of 392 students (aged 12–13 years). The three lesson module dealt with mathematical phenomena providing participants with the commercially available hands-on construction kit, aiming to advance STEAM education. Pupils built original, personal, and individual geometrical structures by using plastic pipes in allowing high levels of creativity as well as of autonomy. Tutors supervised the construction process and intervened only on demand. A pre-/post-test design monitored the cognitive knowledge and the variables of relative autonomy, visual reasoning, formal operations as well as creativity. Our informal intervention produced newly acquired cognitive knowledge which as a process was shown of being supported by a broad basis of (soft) factors as described above. A path analysis elaborated the role of creativity (measured with two subscale: act and flow) to cognitive learning (post-knowledge), when flow was shown to lead. Pre-knowledge scores were significantly influenced by both creativity subscales: act and flow. However, relative autonomy, visual reasoning and formal operations contributed, too. In consequence, cognitive learning within STEAM modules was shown dependent on external triggers. Conclusions for appropriate educational settings to foster STEAM environments are discussed.

Veronika Katermina / Катермина Вероника Викторовна, Anna Gnedash / Гнедаш Анна Александровна

The study is dedicated to the analysis of the features of the formation of online fan discourse in asynchronous multimodal discursive fields on the Internet on the example of football communities in the social network vk.com. The empirical base of the study was network data (posts on community and group walls, comments on posts, statistics on likes of posts and comments, statistics on reposts, popular posts) obtained from the 3 most popular Russian football-themed online communities and uploaded through the vk.com API interface. On the basis of the processed network data the discursive fields of football communities were built and analyzed. This allowed for describing culturally significant concepts and the scenarios of communicative behavior of football fans conditioned by them, as well as to identify universal and specific scenarios of communicative patterns of behavior in the fan culture. Исследование посвящено анализу особенностей формирования сетевого фанатского дискурса в асинхронных мультимодальных дискурсивных полях в сети Интернет на примере футбольных сообществ в социальной сети ВКонтакте. Эмпирической базой исследования стали сетевые данные (посты на стене сообществ и групп, комментарии к постам, статистика лайков постов и комментариев, статистика репостов, популярные посты), полученные из 3 самых популярных российских сетевых сообществ, посвящённых футбольной тематике и выгруженные через интерфейс API ВКонтакте (Топ-100 сообщений-постов и около 500 000 комментариев к ним за период с 1 января 2022 г. по 31 августа 2022 г.). Три полученных дата-сета были подвергнуты процедурам Data Science, математического моделирования, реляционной социологии, корпусной лингвистики и лингводискурсивного анализа. На основе обработанных сетевых данных были построены и проанализированы дискурсивные поля футбольных сообществ. Это позволило описать культурно значимые концепты и обусловленные ими сценарии коммуникативного поведения футбольных фанатов, а также выявить универсальные и специфические сценарии коммуникационных паттернов поведения в фанатской культуре.

Luiza Wollinger Delfino, Esther Império Hamburger, Cecilia Mello et al.

Em antecipação à sua visita a São Paulo em dezembro de 2023, a Significação: Revista de Cultura Audiovisual realizou uma entrevista online de duas horas com Giuliana Bruno, com foco em Atmospheres of Projection e em suas outras contribuições inovadoras. Bruno é palestrante convidada do workshop interdisciplinar organizado pela Fundação de Amparo à Pesquisa do Estado de São Paulo (Fapesp) em dezembro de 2023. Antes disso, ministrará uma Masterclass na Universidade de São Paulo (USP), evento promovido pelo Laboratório de Investigação e Crítica Audiovisual (Laica) e pela Significação: Revista de Cultura Audiovisual, com o apoio da Fapesp, do Instituto de Estudos Avançados (IEA-USP), do Programa de Pós-Graduação em Meios e Processos Audiovisuais da Escola de Comunicações e Artes (PPGMPA-ECA) e do Programa de Pós-Graduação e m Multimeios da Universidade Estadual de Campinas (PPGM-Unicamp).

Diederik Aerts, Jonito Aerts Argëlles, Lester Beltran et al.

In physics, entanglement 'reduces' the entropy of an entity, because the (von Neumann) entropy of, e.g., a composite bipartite entity in a pure entangled state is systematically lower than the entropy of the component sub-entities. We show here that this 'genuinely non-classical reduction of entropy as a result of composition' also holds whenever two concepts combine in human cognition and, more generally, it is valid in human culture. We exploit these results and make a 'new hypothesis' on the nature of entanglement, namely, the production of entanglement in the preparation of a composite entity can be seen as a 'dynamical process of collaboration between its sub-entities to reduce uncertainty', because the composite entity is in a pure state while its sub-entities are in a non-pure, or density, state, as a result of the preparation. We identify within the nature of this entanglement a mechanism of contextual updating and illustrate the mechanism in the example we analyze. Our hypothesis naturally explains the 'non-classical nature' of some quantum logical connectives, as due to Bell-type correlations.

Salvador Bará, Raul C. Lima

Wind farm lights are a conspicuous feature in the nocturnal landscape. Their presence is a source of light pollution for residents and the environment, severely disrupting in some places the aesthetic, cultural, and scientific values of the pristine starry skies. In this work we present a simple model for quantifying the visual impact of individual wind turbine lights, based on the comparison of their brightnesses with the brightness of well-known night sky objects. The model includes atmospheric and visual variables, and for typical parameters it shows that medium-intensity turbine lights can be brighter than Venus up to ~4 km from the turbine, brighter than alpha CMa (the brightest star on the nighttime sky) until about ~10 km, and reach the standard stellar visibility limit for the unaided eye (m_v=+6.00) at ~38 km. These results suggest that the visual range of wind farms at nighttime may be significantly larger than at daytime, a factor that should be taken into account in environmental impact assessments.

Jun Zhu, Jiandong Jin, Zihan Yang et al.

Existing pedestrian attribute recognition (PAR) algorithms are mainly developed based on a static image. However, the performance is not reliable for images with challenging factors, such as heavy occlusion, motion blur, etc. In this work, we propose to understand human attributes using video frames that can make full use of temporal information. Specifically, we formulate the video-based PAR as a vision-language fusion problem and adopt pre-trained big models CLIP to extract the feature embeddings of given video frames. To better utilize the semantic information, we take the attribute list as another input and transform the attribute words/phrase into the corresponding sentence via split, expand, and prompt. Then, the text encoder of CLIP is utilized for language embedding. The averaged visual tokens and text tokens are concatenated and fed into a fusion Transformer for multi-modal interactive learning. The enhanced tokens will be fed into a classification head for pedestrian attribute prediction. Extensive experiments on a large-scale video-based PAR dataset fully validated the effectiveness of our proposed framework.

Dominik Vietinghoff, Michael Böttinger, Gerik Scheuermann et al.

An important task in visualization is the extraction and highlighting of dominant features in data to support users in their analysis process. Topological methods are a well-known means of identifying such features in deterministic fields. However, many real-world phenomena studied today are the result of a chaotic system that cannot be fully described by a single simulation. Instead, the variability of such systems is usually captured with ensemble simulations that produce a variety of possible outcomes of the simulated process. The topological analysis of such ensemble data sets and uncertain data, in general, is less well studied. In this work, we present an approach for the computation and visual representation of confidence intervals for the occurrence probabilities of critical points in ensemble data sets. We demonstrate the added value of our approach over existing methods for critical point prediction in uncertain data on a synthetic data set and show its applicability to a data set from climate research.

Jingfei Xia, Mingchen Zhuge, Tiantian Geng et al.

Figure skating scoring is challenging because it requires judging the technical moves of the players as well as their coordination with the background music. Most learning-based methods cannot solve it well for two reasons: 1) each move in figure skating changes quickly, hence simply applying traditional frame sampling will lose a lot of valuable information, especially in 3 to 5 minutes long videos; 2) prior methods rarely considered the critical audio-visual relationship in their models. Due to these reasons, we introduce a novel architecture, named Skating-Mixer. It extends the MLP framework into a multimodal fashion and effectively learns long-term representations through our designed memory recurrent unit (MRU). Aside from the model, we collected a high-quality audio-visual FS1000 dataset, which contains over 1000 videos on 8 types of programs with 7 different rating metrics, overtaking other datasets in both quantity and diversity. Experiments show the proposed method achieves SOTAs over all major metrics on the public Fis-V and our FS1000 dataset. In addition, we include an analysis applying our method to the recent competitions in Beijing 2022 Winter Olympic Games, proving our method has strong applicability.