145 research outputs found
Art, Visual Illusions, and Data Visualization (Dagstuhl Seminar 24301)
No full textThis report presents the program and outcomes of Dagstuhl Seminar 24301, titled "Art, Visual Illusions, and Data Visualization." The seminar explored the intersection of art, visual illusions, and data science - three distinct yet interconnected disciplines that share a focus on visual representation and perception. Art serves as a medium for storytelling and complex visual communication, while visual illusions offer insights into cognitive and perceptual mechanisms. Data science complements these fields with advanced methods for analyzing and visualizing complex datasets. The seminar examined historical and contemporary examples of the interplay between these domains, showcasing artists such as M.C. Escher, Bridget Riley, and Yayoi Kusama, as well as modern practitioners like Laurie Frick, Refik Anadol, and Giorgia Lupi. These examples illustrate how visual illusions and data visualization techniques have been used to challenge perceptions, uncover hidden patterns, and foster deeper understanding. By bringing together experts in art, cognitive psychology, and data science, the seminar fostered interdisciplinary dialogue and collaboration. Participants explored innovative approaches to visual storytelling and data communication, emphasizing the potential of integrating artistic methods, perceptual insights, and computational tools to create engaging and intuitive visualizations. The seminar highlighted the rich synergies at the intersection of these fields, advancing both theory and practice in visual representation and perception
Perception in Network Visualization (Dagstuhl Seminar 23051)
No full textNetworks are used to model and represent data in many application areas from life sciences to social sciences. Visual network analysis is a crucial tool to improve the understanding of data sets and processes over many levels of complexity, such as different semantic, spatial and temporal granularities. While there is a great deal of work on the algorithmic aspects of network visualization and the computational complexity of the underlying problems, the role and limits of human perception are rarely explicitly investigated and taken into account when designing network visualizations. To address this issue, this Dagstuhl Seminar raised awareness in the network visualization community of the need for more extensive theoretical and empirical understanding of how people perceive and make sense of network visualizations and the significant potential for improving current solutions when perception-based strategies are employed. Likewise, the seminar increased awareness in the perception community that challenges in network research can drive new questions for perception research, for example, in identifying features and patterns in large, often time-varying networks. We brought together researchers from several different communities to initiate a dialogue, foster exchange, discuss the state of the art at this intersection and within the respective fields, identify promising research questions and directions, and start working on selected problems
A fuzzy mdel for scene decomposition based on preattentive visual features
No full textFeature detectors in the early preattentive stage of the Human Visual System (HVS) are believed to cause regions of the viewing field to be identified as perceptually salient, attracting the attention of the viewer. It is anticipated that this characteristic of the HVS can be incorporated into a feature based fuzzy scene decomposition model, which will assist an image rendering system in the allocation of the highest levels of detail to the most conspicuous objects. Efficiency gains should occur, with minimal loss of perceptual image quality. \ud
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This paper describes the early stages of the development of this fuzzy model, for a small subset of commonly accepted visual features: colour, size, location, edges and depth cues. Previous researchers have used arbitrary feature relationship models in image processing systems, with some success. Our aim is to improve on these models by integrating present knowledge of visual feature relationships , with experimental results of our own, and to apply this model to the area of image synthesis.\ud
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Preliminary results from experiments with size features are presented, along with planned experimentation for other visual features. This work will have applications in the areas of scientific visualisation, vision simulation and entertainment
A framework for the study of vision in active observers
No full textWe present a framework for the study of active vision, i.e., the functioning of the visual system during actively self-generated body movements. In laboratory settings, human vision is usually studied with a static observer looking at static or, at best, dynamic stimuli. In the real world, however, humans constantly move within dynamic environments. The resulting visual inputs are thus an intertwined mixture of self- and externally-generated movements. To fill this gap, we developed a virtual environment integrated with a head-tracking system in which the influence of self- and externally-generated movements can be manipulated independently. As a proof of principle, we studied perceptual stationarity of the visual world during lateral translation or rotation of the head. The movement of the visual stimulus was thus parametrically tethered to self-generated movements. We found that estimates of object stationarity were less biased and more precise during head rotation than translation. In both cases the visual stimulus had to partially follow the head movement to be perceived as immobile. We discuss a range of possibilities for our setup among which the study of shape perception in active and passive conditions, where the same optic flow is replayed to stationary observers
Synthetic environments as visualization method for product design
No full textIn this paper, we explored the use of low fidelity Synthetic Environments (SE; i.e., a combination of simulation techniques) for product design. We explored the usefulness of low fidelity SE to make design problems explicit. In particular, we were interested in the influence of interactivity on user experience. For this purpose, an industrial design case was taken: the innovation of an airplane galley. A virtual airplane was created in which an interactive model of the galley was placed. First, three groups of participants explored the SE in different conditions: Participants explored the SE interactively (Interactive condition), watched a recording (Passive Dynamic condition), or watched static images (Passive Static condition). Afterwards, participants were tested in a questionnaire on how accurately they had memorized the spatial layout of the SE. The results revealed that interactive SE does not necessarily provoke participants to memorize spatial layouts more accurately. However, the effect of interactive learning is dependent on the participants’ Visual Spatial Ability (VSA). Consequently, this finding supports use of interactive exploration of prototypes through low fidelity SE for the product design cycle when taking the individual’s characteristics into accountHuman Information Communication DesignIndustrial Design Engineerin
Bernice E. Newell, Tacoma, Washington, approximately 1899
No full textCaption on mount: A. L. Jackson. 919 C. Street. Tacoma, Wash. Paris Panel.
Handwritten on mount: Bernice E. Newell. Journalist. Author of "The Mountain."
Handwritten on verso: Wife Bernice Newell
PH Coll 334 AL Jackson. 1Albert L. Jackson was active in Eugene and Portland, Oregon from 1878 to 1887. He then moved to Tacoma, Washington where he worked from 1891 until 1917.To order a reproduction, inquire about permissions, or for information about prices see:
http://www.lib.washington.edu/specialcollections/services/reproduction/reproduction
Please cite the Order Numbe
Data Physicalization (Dagstuhl Seminar 18441)
No full textData physicalization involves representing numbers and relationships using physical, tangible displays. These displays provide tactile, as well as visual metaphors for expressing and experiencing data, and can unlock new analytical insights and emotional responses. This Dagstuhl seminar brought together a diverse group of researchers and practitioners to explore the benefits and challenges of physicalization - computer scientists trained in visualization, virtual reality and human-computer interaction; architects of virtual and augmented systems; perceptual and cognitive scientists; and artists and designers. Through interactive discussions and demonstrations, we explored physicalization, as a set of methodologies for representing data, for engaging audiences, and for artistic expression
Human-Centered Content-Based Image Retrieval
No full textA breakthrough is needed in order to achieve a substantial progress in the field of Content-Based Image Retrieval (CBIR). This breakthrough can be enforced by: 1) optimizing user-system interaction, 2) combining the wealth of techniques from text-based Information Retrieval with CBIR techniques, 3) exploiting human cognitive characteristics, especially human color processing, and 4) conducting benchmarks with users for evaluating new CBIR techniques. In this paper, these guidelines are illustrated by findings from our research conducted the last five years, which have lead to the development of the online Multimedia for Art ReTrieval (M4ART) system: http://www.m4art.org. The M4ART system follows the guidelines on all four issues and is assessed on benchmarks using 5730 queries on a database of 30,000 images. Therefore, M4ART can be considered as a first step into a new era of CBIR
Fully automatic perceptual modeling of near regular textures
No full textNear regular textures feature a relatively high degree of regularity. They can be conveniently modeled by the combination of a suitable set of textons and a placement rule. The main issues in this respect are the selection of the minimum set of textons bringing the variability of the basic patterns; the identification and positioning of the generating lattice; and the modelization of the variability in both the texton structure and the deviation from periodicity of the lattice capturing the naturalness of the considered texture. In this contribution, we provide a fully automatic solution to both the analysis and the synthesis issues leading to the generation of textures
samples that are perceptually indistinguishable from the original ones. The definition of an ad-hoc periodicity index allows to predict the suitability of the model for a given texture. The model is validated through psychovisual experiments providing the conditions for subjective equivalence among the original and synthetic textures,
while allowing to determine the minimum number of textons to be used to meet such a requirement for a given texture class. This is of prime importance in model-based coding applications, as is the one we foresee, as it allows to minimize the amount of information to be transmitted to the receiver
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