Many disciplines spend considerable resources studying behavior. Tools range from pen-and-paper observation to biometric sensing. A tool's appropriateness depends on the goal and justification of the study, the observable context and feature set of target behaviors, the observers' resources, and the subjects' tolerance to intrusiveness. We present two systems: Viz-A-Vis and Tableau Machine. Viz-A-Vis is an analytical tool appropriate for onsite, continuous, wide-coverage and long-term capture, and for objective, contextual, and detailed analysis of the physical actions of subjects who consent to overhead video observation. Tableau Machine is a creative artifact for the home. It is a long-lasting, continuous, interactive, and abstract Art installation that captures overhead video and visualizes activity to open opportunities for creative interpretation. We focus on overhead video observation because it affords a near one-to-one correspondence between pixels and floor plan locations, naturally framing the activity in its spatial context. Viz-A-Vis is an information visualization interface that renders and manipulates computer vision abstractions. It visualizes the hidden structure of behavior in its spatiotemporal context. We demonstrate the practicality of this approach through two user studies. In the first user study, we show an important search performance boost when compared against standard video playback and against the video cube. Furthermore, we determine a unanimous user choice for overviewing and searching with Viz-A-Vis. In the second study, a domain expert evaluation, we validate a number of real discoveries of insightful environmental behavior patterns by a group of senior architects using Viz-A-Vis. Furthermore, we determine clear influences of Viz-A-Vis over the resulting architectural designs in the study. Tableau Machine is a sensing, interpreting, and painting artificial intelligence. It is an Art installation with a model of perception and personality that continuously and enduringly engages its co-occupants in the home, creating an aura of presence. It perceives the environment through overhead cameras, interprets its perceptions with computational models of behavior, maps its interpretations to generative abstract visual compositions, and renders its compositions through paintings. We validate the goal of opening a space for creative interpretation through a study that included three long-term deployments in real family homes.

Ambient displays present useful information in the periphery of the users and normally they don’t support interactions. Technological advancements in digital displays, computing power of smart phones and faster wireless networks enable new forms of interactions. The purpose of this thesis is to explore the design space of ambient displays and make an inquiry into the future state by designing and implementing an interactive prototype for a specific use case. The context of the project is a music management company, its Artist & Repertoire division and their work-flow. The work introduces a novel concept of Interactive Semi-Ambient Displays with Narrative visualization features. The thesis is a comprehensive documentation of an iterative Research through Design process and its final outcome, an interactive prototype. The prototype consists of a Semi-Ambient visualization, integrated with narrative features and a mobile application to interact and control the visualization. A formative focus group evaluation of the prototype was conducted to evaluate the final outcome of the process. Results suggest that the concept is a viable way to effectively visualize information in office environments and support the work-flow of co-located groups. Based on the comments, future directions for the general concept and the project are discussed. / Ambivalenta skärmar ger nyttig information i periferin hos användarna som normalt inte stöder en interaktion. Tekniska framsteg i de digitala skärmarna, datorkapaciteten i smarta telefoner och snabbare trådlösa nätverk möjliggör en ny form av interaktion. Syftet med denna avhandling är att undersöka utformningen av dessa ambivalenta skärmar och redogöra om ett framtida skede genom att utforma och genomföra en interaktiv prototyp hos ett specifikt användningsområde. Projektets kontext är ett förvaltningsbolag i musikbranschen, och dess Konstär & Repertoar indelning samt deras arbetsflöde. Arbetets syfte är att introducera ett nytt koncept av interaktiva Semi-Ambivalenta skärmar med berättande visualiseringsfunktioner. Avhandlingen är en omfattande sammansättning av en återkommande forskning inom design process och dess slutliga resultat, en interaktiv prototyp. Prototypen består av en Semi-Ambivalent visualisering, integrerad med narrativa funktioner och en mobil applikation för att interagera och styra visualisering. En utvärdering av prototypen utfördes i form av en pedagogisk fokusgrupp för att ta fram det slutliga resultatet av processen. Resultaten tyder på att konceptet är ett lönsamt sätt att effektivt visualisera information i kontorsmiljöer och stödja arbetsflödet hos lokala arbetsgrupper. Baserat på kommentarerna som finns, är de framtida målen för det grundliga konceptet & projektet att föra en diskussion.

Thesis (M. Tech. Design technology) -- Central University of Technology, Free State, 2011 / This dissertation outlines a procedural scanning process using the portable ZCorporation ZScanner® 700 and provides an overview of the developments surrounding 3D scanning technologies; specifically their application for archiving Cultural Heritage sites and projects. The procedural scanning process is structured around the identification of 3D data recording variables applicable to the digital archiving of an art museum’s collection of sculptures. The outlining of a procedural 3D scanning environment supports the developing technology of 3D digital archiving in view of artefact preservation and interactive digital accessibility. Presented in this paper are several case studies that record 3D scanning variables such as texture, scale, surface detail, light and data conversion applicable to varied sculptural surfaces and form. Emphasis is placed on the procedural documentation and the anomalies associated with the physical object, equipment used, and the scanning environment. In support of the above, the Cultural Heritage projects that are analyzed prove that 3D portable scanning could provide digital longevity and access to previously inaccessible arenas for a diverse range of digital data archiving infrastructures. The development of 3D data acquisition via scanning, CAD modelling and 2D to 3D data file conversion technologies as well as the aesthetic effect and standards of digital archiving in terms of the artwork – viewer relationship and international practices or criterions of 3D digitizing are analysed. These projects indicate the significant use of optical 3D scanning techniques and their employ on renowned historical artefacts thus emphasizing their importance, safety and effectiveness. The aim with this research is to establish that the innovation and future implications of 3D scanning could be instrumental to future technological advancement in an interdisciplinary capacity to further data capture and processing in various Cultural Heritage diagnostic applications.

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Visualization tools are frequently used to help people understand everyday data in their lives. One such example is visualization in behaviour feedback tools. Behaviour feedback tools are used to try to help people improve their health or personal well-being or to carry out sound environmental sustainability practices. However, understanding and reasoning about personal data (e.g., pedometer counts, blood pressure readings or home electricity consumption) or gaining a deeper understanding of one's current practices and learning how to make a change can be challenging when using data alone. My literature review of this field showed that two of the main challenges in actual practice are providing a context in which to reason about the data and reducing the cost of maintenance to fit those tools into everyday life routines. Thus, I propose to integrate time-varying feedback data within a personal digital calendar. This combination of calendar and feedback data can provide contextual information to interpret data and make the data accessible in an attentionally ambient way that is suitable for maintaining awareness. I propose that the familiarity and common practice of using digital calendars can minimize the cost of learning and maintenance for people and easily fit into one's daily life routines. The viability of this approach was confirmed in my quantitative lab experiments. The results showed that visualization of feedback data integrated on a digital calendar is comprehensible, and it does not interfere with regular calendar use with proper visual encodings. After confirming the viability of my proposal, I implemented the on-calendar visualization as a web application that was synchronized with Google Calendar API and a real-time feedback data stream. To further investigate this approach in a real life situation, I deployed the application in the field for longitudinal field studies: two case studies as pilot deployment and an eight-week field study. Results showed that people liked the idea of integrating feedback data into their personal digital calendars. It required a low cost in learning and maintenance. The calendar events provided rich context for people to visualize and reason about their feedback data. The design enabled people to quickly identify and explain repeated patterns and anomalies. Meanwhile, I found that people's existing information use habits (in this case, how they use digital calendars) can highly influence the effectiveness of the feedback design. Moreover, I derived a feedback model that identifies basic components in feedback design and illustrates the role of feedback tools. With that I articulated possible design barriers that could prevent ongoing use of feedback tools. Reflecting on the effects of the on-calendar design approach, I discussed design implications inspired by this work. This work introduces a reflective approach in feedback design that can easily fit into people's existing information ecosystem (specifically, a personal digital calendar in this work). The main contributions of this thesis are: the first systematic literature review of personal visualization design used in everyday life; the design and implementation of an on-calendar design that integrates feedback data on people's personal digital calendars to provide context for reasoning and support easy access for ongoing use; the extended definition of ambience from spatial location to attentional demand; a viability study to confirm the on-calendar design approach; longitudinal studies to investigate the effects of the on-calendar design approach and the feedback model of design mechanism to inspect ongoing factors in feedback designs. / Graduate / 0984, 0384 / dhuangca@gmail.com

The digitalisation of information now affects most fields of human activity. From the social sciences to biology to physics, the volume, velocity, and variety of data exhibit exponential growth trends. With such rates of expansion, efforts to understand and make sense of datasets of such scale, how- ever driven and directed, progress only at an incremental pace. The challenges are significant. For instance, the ability to display an ever growing amount of data is physically and naturally bound by the dimensions of the average sized display. A synergistic interplay between statistical analysis and visualisation approaches outlines a path for significant advances in the field of data exploration. We can turn to statistics to provide principled guidance for prioritisation of information to display. Using statistical results, and combining knowledge from the cognitive sciences, visual techniques can be used to highlight salient data attributes. The purpose of this thesis is to explore the link between computer science, statistics, visualization, and the cognitive sciences, to define and develop more systematic approaches towards the design of glyphs. Glyphs represent the variables of multivariate data records by mapping those variables to one or more visual channels (e.g., colour, shape, and texture). They offer a unique, compact solution to the presentation of a large amount of multivariate information. However, composing a meaningful, interpretable, and learnable glyph can pose a number of problems. The first of these problems exist in the subjectivity involved in the process of data to visual channel mapping, and in the organisation of those visual channels to form the overall glyph. Our first contribution outlines a computational technique to help systematise many of these otherwise subjective elements of the glyph design process. For visual information compression, common patterns (motifs) in time series or graph data for example, may be replaced with more compact, visual representations. Glyph-based techniques can provide such representations that can help users find common patterns more quickly, and at the same time, bring attention to anomalous areas of the data. However, replacing any data with a glyph is not going to make tasks such as visual search easier. A key problem is the selection of semantically meaningful motifs with the potential to compress large amounts of information. A second contribution of this thesis is a computational process for systematic design of such glyph libraries and their subsequent glyphs. A further problem in the glyph design process is in their evaluation. Evaluation is typically a time-consuming, highly subjective process. Moreover, domain experts are not always plentiful, therefore obtaining statistically significant evaluation results is often difficult. A final contribution of this work is to investigate if there are areas of evaluation that can be performed computationally.

We are entering an era of business intelligence and big data where simple tables and other traditional means of data display cannot deal with the vast amounts of data required to meet the decision-making needs of businesses and their clients. Graphical figures constructed with modern visualization software can convey more information than a table because there is a limit to the table size that is visually usable. Contemporary decision performance is influenced by the task domain, the user experience, and the visualizations themselves. Utilizing data visualization in task performance to aid in decision making is a complex process. We develop and test a decision-making framework to examine task performance in a visual and non-visual aided decision-making by using three experiments to test this framework. Studies 1 and 2 investigate DV formats and how complexity and design affects the proposed visual decision making framework. The studies also examine how DV formats affect task performance, as measured by accuracy and timeliness, and format preference. Additionally, these studies examine how DV formats influence the constructs in the proposed decision making framework which include information usefulness, decision confidence, cognitive load, visual aesthetics, information seeking intention, and emotion. Preliminary findings indicate that graphical DV allows individuals to respond faster and more accurately, resulting in improved task fit and performance. Anticipated implications of this research are as follows. Visualizations are independent of the size of the data set but can be increasingly complex as the data complexity increases. Furthermore, well designed visualizations let you see through the complexity and simultaneously mine the complexity with drill down technologies such as OLAP.

Many disciplines spend considerable resources studying behavior. Tools range from pen-and-paper observation to biometric sensing. A tool's appropriateness depends on the goal and justification of the study, the observable context and feature set of target behaviors, the observers' resources, and the subjects' tolerance to intrusiveness. We present two systems: Viz-A-Vis and Tableau Machine. Viz-A-Vis is an analytical tool appropriate for onsite, continuous, wide-coverage and long-term capture, and for objective, contextual, and detailed analysis of the physical actions of subjects who consent to overhead video observation. Tableau Machine is a creative artifact for the home. It is a long-lasting, continuous, interactive, and abstract Art installation that captures overhead video and visualizes activity to open opportunities for creative interpretation. We focus on overhead video observation because it affords a near one-to-one correspondence between pixels and floor plan locations, naturally framing the activity in its spatial context. Viz-A-Vis is an information visualization interface that renders and manipulates computer vision abstractions. It visualizes the hidden structure of behavior in its spatiotemporal context. We demonstrate the practicality of this approach through two user studies. In the first user study, we show an important search performance boost when compared against standard video playback and against the video cube. Furthermore, we determine a unanimous user choice for overviewing and searching with Viz-A-Vis. In the second study, a domain expert evaluation, we validate a number of real discoveries of insightful environmental behavior patterns by a group of senior architects using Viz-A-Vis. Furthermore, we determine clear influences of Viz-A-Vis over the resulting architectural designs in the study. Tableau Machine is a sensing, interpreting, and painting artificial intelligence. It is an Art installation with a model of perception and personality that continuously and enduringly engages its co-occupants in the home, creating an aura of presence. It perceives the environment through overhead cameras, interprets its perceptions with computational models of behavior, maps its interpretations to generative abstract visual compositions, and renders its compositions through paintings. We validate the goal of opening a space for creative interpretation through a study that included three long-term deployments in real family homes. / <p>QC 20160405</p>

Evaluating the “success” of an information visualization (InfoVis) where its main purpose is communication or presentation is challenging. Within metrics that go beyond traditional analysis- and performance-oriented approaches, one construct that has received attention in recent years is “user engagement”. In this research, I propose Affective Engagement (AE)-- user's engagement in emotional aspects as a metric for InfoVis evaluation. I developed and evaluated a self-report measurement tool named AEVis that can quantify a user's level of AE while using an InfoVis. Following a systematic process of evidence-centered design, each activity during instrument development contributed specific evidence to support the validity of interpretations of scores from the instrument. Four stages were established for the development: In stage 1, I examined the role and characteristics of AE in evaluating information visualization through an exploratory qualitative study, from which 11 indicators of AE were proposed: Fluidity, Enthusiasm, Curiosity, Discovery, Clarity, Storytelling, Creativity, Entertainment, Untroubling, Captivation, and Pleasing; In stage 2, I developed an item bank comprising various candidate items for assessing a user's level of AE, and assembled the first version of survey instrument through target population and domain experts' feedback; In stage 3, I conducted three field tests for instrument revisions. Three analytical methods were applied during this process: Item Analysis, Factor Analysis (FA), and Item Response Theory (IRT); In stage 4, a follow-up field test study was conducted to investigate the external relations between constructs in AEVis and other existing instruments. The results of the four stages support the validity and reliability of the developed instrument, including: In stage 1, user's AE characteristics elicited from the observations support the theoretical background of the test content; In stage 2, the feedback and review from target users and domain experts provides validity evidence for the test content of the instrument in the context of InfoVis; In stage 3, results from Exploratory and Confirmatory FA, as well as IRT methods reveal evidence for the internal structure of the instrument; In stage 4, the correlations between total scores and sub-scores of AEVis and other existing instruments provide external relation evidence of score interpretations. Using this instrument, visualization researchers and designers can evaluate non-performance-related aspects of their work efficiently and without specific domain knowledge. The utilities and implications of AE can be investigated as well. In the future, this research may provide foundation for expanding the theoretical basis of engagement in the fields of human-computer interaction and information visualization.

Object recognition is imperfect; often incomplete processing or deprived information yield misperceptions (i.e., misidentification) of objects. While quickly rectified and typically benign, instances of such errors can produce dangerous consequences (e.g., police shootings). Through a series of experiments, this study examined the competitive process of multiple object interpretations (candidates) during the earlier stages of object recognition process using a lexical decision task paradigm. Participants encountered low-pass filtered objects that were previously demonstrated to evoke multiple responses: a highly frequented interpretation (“primary candidates”) and a lesser frequented interpretation (“secondary candidates”). When objects were presented without context, no facilitative effects were observed for primary candidates. However, secondary candidates demonstrated evidence for being actively suppressed. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection