While autonomous vehicles have the potential to fundamentally reshape transportation and daily life, their current technological limitations require human intervention through teleoperation to handle complex situations. These situations can range from unexpected road obstacles and complex traffic patterns to emergency scenarios that exceed the vehicle’s autonomous decision-making capabilities. In such cases, remote operators must take control of the vehicle, making tele-driving a critical component of autonomous vehicle systems. Tele-driving requires high situational awareness (SA) to ensure safety and prevent accidents. This study investigates the effectiveness of incorporating a bird’s eye view (BEV) in tele-driving interfaces. Through two comprehensive experiments, we compared a regular frontal view with different arrangements of BEV added to it. Our findings indicate that adding a BEV does not enhance the tele-driver’s SA and may even impair the perception of critical environmental elements in certain scenarios. The findings provide valuable insights for the design of tele-driving interfaces.

While autonomous vehicles (AVs) continue to advance and reshape modern transportation, they remain unable to navigate all traffic conditions without human input, highlighting the need for remote human intervention in edge-case scenarios. Two major teleoperation paradigms have emerged to address this need: tele-driving and tele-assistance. In tele-driving, remote operators (ROs) continuously control the AV through direct access to its actuators. In tele-assistance, ROs provide high-level instructions through a specialized interface, with low-level maneuvers delegated to the AV. We conducted a quantitative comparison of these paradigms, examining four edge-case scenarios: one uses a steering wheel and pedals, the other employs discrete high-level commands through a Wizard-of-Oz methodology. We measured mental workload, situation awareness, time completion, and overall user experience (UX). Results indicate that the tele-assistance interface reduced operators’ mental workload and improved situation awareness, suggesting the need for further development of tele-assistance interfaces.

Interactive systems that explain data, or support decision making often emphasize what is present while overlooking what is expected but missing. This presence bias limits users’ ability to form complete mental models of a dataset or situation. Detecting absence depends on expectations about what should be there, yet interfaces rarely help users form such expectations. We present an experimental study examining how reference framing and prompting influence people’s ability to recognize expected but missing categories in datasets. Participants compared distributions across three domains (energy, wealth, and regime) under two reference conditions: Global, presenting a unified population baseline, and Partial, showing several concrete exemplars. Results indicate that absence detection was higher with Partial reference than with Global reference, suggesting that partial, samples-based framing can support expectation formation and absence detection. When participants were prompted to look for what was missing, absence detection rose sharply. We discuss implications for interactive user interfaces and expectation-based visualization design, while considering cognitive trade-offs of reference structures and guided attention.

Augmented reality (AR) applications have been shown to improve accessibility for people with low vision by enhancing the visibility of surrounding objects. Yet, prior studies mostly examined controlled settings and often focused on developing solutions for specific functional challenges. A human remote assistant powered with AR capabilities may provide a flexible solution that addresses a variety of scenarios. To examine how AR-based remote assistance can help low-vision people in real-world settings, we examined the scenario of visiting a museum, which requires coping with a variety of tasks, from navigating between museum rooms to the accessibility of museum exhibits. We conducted a qualitative user study at an archeological museum with 11 low-vision participants who toured a predefined path while receiving real-time auditory explanations and AR annotations from a remote assistant. Our results reveal that the AR-based remote assistance improved the museum experience, assisting in mobility within the museum and the visibility of artifacts. The use of remote assistance proved to be dynamic and flexible, enabling real-time in-place annotations that helped guide low-vision participants, providing a stronger feeling of security. While acknowledging the transformative potential, participants highlighted challenges in accuracy and responsiveness, emphasizing the need to improve the design of real-time AR annotations. Our study is the first to examine the use of AR remote assistance in meeting the dynamic and diverse needs of people with low vision, illustrating both its potential and the challenges for this population.

Abstract Augmented reality (AR) introduces new dynamics for personal information sharing by embedding digital content into shared physical spaces. While prior work has examined comfort and privacy concerns in AR, less is known about why people choose to disclose personal information and how social context shapes these decisions. We conducted a mixed-methods study with 20 participants across three fictional scenarios that varied in formality and social norms. Participants disclosed information to clarify identity, build relationships, and strategically manage impressions, yet patterns varied by setting: intimate details were sometimes shared in casual contexts despite acknowledged risks, while professional contexts raised concerns about appropriateness. Based on these findings, we present an AR-adapted disclosure decision model that treats context as an active moderator of perceived risks and benefits and highlights the roles of control and reciprocity in co-present environments. We conclude with design recommendations for context-sensitive privacy mechanisms that support selective and reciprocal disclosure in AR.

Virtual museum tours are increasingly used to expand access to cultural heritage, yet their experiential equivalence to physical visits remains unclear. This study compared user experience in physical and virtual tours of the same museum exhibition. Thirty-two participants explored either the physical exhibition or an photo-based 360° virtual tour and completed standardized and custom questionnaires. No significant differences were observed on experiential scales between conditions. However, results revealed distinct spatial usability effects: the physical tour yielded higher ratings for navigation ease, orientation, and backtracking. These results indicate that high-quality virtual tours may replicate some experiential aspects of physical visits but still present challenges in spatial clarity and intuitive wayfinding. The findings contribute insight into where current virtual museum technologies show similarities and differences in navigation, satisfaction, and accessibility in digital heritage experiences.

Autonomous vehicles (AVs) are rapidly evolving as a novel way of transportation. Nevertheless, there is a consensus that AVs cannot address all traffic scenarios independently. Consequently, there arises a need for remote human intervention. To pave the way for large-scale deployment of AVs onto public roadways, innovative models of remote operation must evolve. Such a paradigm is Tele-assistance, which posits that the low-level control of AVs should be delegated through high-level commands. Our work explores how such a command language should be constructed as a first step in designing a Tele-assistance user interface. Through interviews with 17 experienced teleoperators, we elicit a set of discrete commands that a remote operator can use to resolve various road scenarios. Subsequently, we create a scenario-command mapping and a thematic classification of the defined commands. Finally, we present an initial Tele-assistance interface design based on these commands.

Technology advancements such as smart glasses offer novel opportunities to interact with technology on-the-go. This study examined use of two types of smart glasses (Everysight Raptor and Vuzix m100) for reading during walking and compared to a mobile phone. Fifty-two healthy adults performed single-task and dual-task walking and reading in one of two environments. Objective measures included gait speed and variability and reading speed and comprehension, and subjective measures included workload and usability. Results indicated that when using smart glasses, participants walked slower and with larger gait variability, read less text and had lower comprehension scores across both environments. Participants perceived the glasses as less usable and more demanding than the phone, with no differences between the two types of glasses. This work provides a benchmark for the negative impact of using smart glasses during walking indoors and outdoors. Potential implications are higher risk for community ambulation, suggesting a need for consideration of human attentional capacity when designing smart glasses interfaces and future urban environments.

Visually encoding quantitative information associated with graph links is an important problem in graph visualization. A conventional approach is to vary the thickness of lines to encode the strength of connections in node-link diagrams. In this paper, we present Sticky Links, a novel visual encoding method that draws graph links with stickiness. Taking the metaphor of links with glues, sticky links represent connection strength using spiky shapes, ranging from two broken spikes for weak connections to connected lines for strong connections. We conducted a controlled user study to compare the efficiency and aesthetic appeal of stickiness with conventional thickness encoding. Our results show that stickiness enables more effective and expressive quantitative encoding while maintaining the perception of node connectivity. Participants also found sticky links to be more aesthetic and less visually cluttering than conventional thickness encoding. Overall, our findings suggest that sticky links offer a promising alternative to conventional methods for encoding quantitative information in graphs.

Teleoperation of autonomous vehicles has been gaining a lot of attention recently and is expected to play an important role in helping autonomous vehicles handle difficult situations which they cannot handle on their own. In such cases, a remote driver located in a teleoperation center can remotely drive the vehicle until the situation is resolved. However, teledriving is a challenging task and requires many cognitive resources from the teleoperator. Our goal is to assist the remote driver in some complex situations by giving the driver appropriate advice. The advice is displayed on the driver’s screen to help her make the right decision. To this end, we introduce the TeleOperator Advisor (TOA), an adaptive agent that provides assisting advice to a remote driver. We evaluate the TOA in a simulation-based setting in two scenarios: overtaking a slow vehicle and passing through a traffic light. Results indicate that our advice helps to reduce the cognitive load of the remote driver and improve driving performance.

Choosing between two or more alternatives, ranging from relatively simple alternatives to more complex ones, is a common and important task. Visualization techniques may help users to examine differences between such alternatives. The potential contribution of an adequate visualization may increase as the comparison becomes more complicated, when the compared alternatives include multiple dimensions, and when they are examined over time. We propose a novel visualization technique designed to represent the temporal evolution of multiple dimensions between two competitors at a glance. We exemplify how the visualization supports the comparison of two events according to their changes in eight discrete emotions over time. We report on a study that compared our suggested visualization with two common visualization techniques. User performance and preferences were measured under a formal task taxonomy, using Twitter data of real-world events. The experimental results indicate the effectiveness of our visualization as demonstrated by task completion time and accuracy.

Autonomous vehicle (AV) technologies are rapidly evolving with the vision of having self-driving cars moving safely with no human input. However, it is clear that at least in the near and foreseeable future, AVs will not be able to resolve all road incidents and that in some situations remote human assistance will be required. However, remote driving is not trivial and introduces many challenges stemming mostly from the physical disconnect of the remote operator. In order to highlight these challenges and understand how to better design AV teleoperation interfaces, we conducted several observations of AV teleoperation sessions as well as in-depth interviews with 14 experts. Based on these interviews, we provide an investigation and analysis of the major AV teleoperation challenges. We follow this by providing design suggestions for the development of future teleoperation interfaces for assistance and driving of AVs.

Appropriate color mapping for categorical data visualization can significantly facilitate the discovery of underlying data patterns and effectively bring out visual aesthetics. Some systems suggest predefined palettes for this task. However, a predefined color mapping is not always optimal, failing to consider users' needs for customization. Given an input categorical data visualization and a reference image, we present an effective method to automatically generate a coloring that resembles the reference while allowing classes to be easily distinguished. We extract a color palette with high perceptual distance between the colors by sampling dominant and discriminable colors from the image's color space. These colors are assigned to given classes by solving an integer quadratic program to optimize point distinctness of the given chart while preserving the color spatial relations in the source image. We show results on various coloring tasks, with a diverse set of new coloring appearances for the input data. We also compare our approach to state-of-the-art palettes in a controlled user study, which shows that our method achieves comparable performance in class discrimination, while being more similar to the source image. User feedback after using our system verifies its efficiency in automatically generating desirable colorings that meet the user's expectations when choosing a reference.

Static visual attributes such as color and shape are used with great success in visual charts designed to be displayed in static, hard-copy form. However, nowadays digital displays become ubiquitous in the visualization of any form of data, lifting the confines of static presentations. In this article, we propose incorporating data-driven animations to bring static charts to life, with the purpose of encoding and emphasizing certain attributes of the data. We lay out a design space for data-driven animated effects and experiment with three versatile effects, marching ants, geometry deformation and gradual appearance. For each, we provide practical details regarding their mode of operation and extent of interaction with existing visual encodings. We examine the impact and effectiveness of our enhancements through an empirical user study to assess preference as well as gauge the influence of animated effects on human perception in terms of speed and accuracy of visual understanding.

One of the fundamental tasks in visualization is to compare two or more visual elements. However, it is often difficult to visually differentiate graphical elements encoding a small difference in value, such as the heights of similar bars in bar chart or angles of similar sections in pie chart. Perceptual laws can be used in order to model when and how we perceive this difference. In this work, we model the perception of Just Noticeable Differences (JNDs), the minimum difference in visual attributes that allow faithfully comparing similar elements, in charts. Specifically, we explore the relation between JNDs and two major visual variables: the intensity of visual elements and the distance between them, and study it in three charts: bar chart, pie chart and bubble chart. Through an empirical study, we identify main effects on JND for distance in bar charts, intensity in pie charts, and both distance and intensity in bubble charts. By fitting a linear mixed effects model, we model JND and find that JND grows as the exponential function of variables. We highlight several usage scenarios that make use of the JND modeling in which elements below the fitted JND are detected and enhanced with secondary visual cues for better discrimination.

Design and co-creation activities around 3D artifacts often require close collocated coordination between multiple users. Augmented reality (AR) technology can support collocated work enabling users to flexibly work with digital objects while still being able to use the physical space for coordination. With most of current research focusing on remote AR collaboration, less is known about collocated collaboration in AR, particularly in relation to interpersonal dynamics between the collocated collaborators. Our study aims at understanding how shared augmented reality facilitated by mobile devices (mobile augmented reality or MAR) affects collocated users' coordination. We compare the coordination behaviors that emerged in a MAR setting with those in a comparable fully physical setting by simulating the same task -of the shared physical dimension for participants' ability to coordinate in the context of collaborative co-creation. Namely, participants working in a fully physical setting were better able to leverage the work artifact itself for their coordination needs, working in a mode that we term artifact-oriented coordination. Conversely, participants collaborating around an AR artifact leveraged the shared physical workspace for their coordination needs, working in what we refer to as space-oriented coordination. We discuss implications for a AR-based collaboration and propose directions for designers of AR tools.

Infographics are engaging visual representations that tell an informative story using a fusion of data and graphical elements. The large variety of infographic design poses a challenge for their high-level analysis. We use the concept of Visual Information Flow (VIF), which is the underlying semantic structure that links graphical elements to convey the information and story to the user. To explore VIF, we collected a repository of over 13K infographics. We use a deep neural network to identify visual elements related to information, agnostic to their various artistic appearances. We construct the VIF by automatically chaining these visual elements together based on Gestalt principles. Using this analysis, we characterize the VIF design space by a taxonomy of 12 different design patterns. Exploring in a real-world infographic dataset, we discuss the design space and potentials of VIF in light of this taxonomy.

There is increasing evidence that user characteristics can have a significant impact on visualization effectiveness, suggesting that visualizations could be enriched with personalization mechanisms that better fit each user's specific needs and abilities. In this paper, we contribute to this body of work with a study that investigates the impact of six user characteristics on the effectiveness of time series visualizations, which was not previously investigated in relation to personalizing Information visualization. We report on a controlled user study that compare four possible time series visualization techniques. User performance and how it was affected by user characteristics was measured while performing tasks from a formal taxonomy using Twitter data about real-world events. Our results show that both the personality trait of locus of control and the cognitive ability of verbal working memory influence which visualization is more effective when dealing with demanding and complex tasks. These findings extend the need for personalization to visualizations for time series data, and we discuss them in the context of creating systems that can utilize knowledge of the user's specific characteristics in order to present the most suitable visualization for each user.

This work proposes Winglets, an enhancement to the classic scatterplot to better perceptually pronounce multiple classes by improving the perception of association and uncertainty of points to their related cluster. Designed as a pair of dual-sided strokes belonging to a data point, Winglets leverage the Gestalt principle of Closure to shape the perception of the form of the clusters, rather than use an explicit divisive encoding. Through a subtle design of two dominant attributes, length and orientation, Winglets enable viewers to perform a mental completion of the clusters. A controlled user study was conducted to examine the efficiency of Winglets in perceiving the cluster association and the uncertainty of certain points. The results show Winglets form a more prominent association of points into clusters and improve the perception of associating uncertainty.

As technology advances, people increasingly interact with virtual objects in settings such as augmented reality (AR) where the virtual layer is superimposed on top of the physical world. Similarly to interactions with physical objects, users may assign virtual objects with value, experience a sense of relatedness, and develop psychological ownership over these objects. The objective of this study is to understand how AR's unique characteristics influences the emergence of meaning and ownership perceptions amongst users. We conducted a study of users' interactions with a virtual dog over a three-week period, comparing AR and fully virtual settings. Our findings show that engagement with the application is a key determinant of the relation users develop with virtual objects. However, the effect of the background layer-whether physical or virtual-dominates the development of relatedness and ownership feelings, highlighting the importance of the "real" physical layer in shaping users' perceptions.

Images are characterized by a complex system of attributes. One of the most elusive properties of an image is its emotiveness – the ability to trigger an emotional reaction in the viewer. Prior research has demonstrated that users react to image emotiveness, yet to date there is little theoretical understanding and scarce empirical evidence as to the role played by emotiveness in the image retrieval process. Our study aims to fill this gap and investigates how users perceive the emotional content of the image-seeking task; explicate this emotional content in search keywords; and react to image emotiveness in selecting relevant images. Using a multimethod approach that combines quantitative and qualitative analyses, we performed three experiments where participants searched for images, both within the predefined set of images and in an open Web environment. Our findings suggest that although seekers rarely explicate image emotiveness in search keywords, their decision to select relevant images is largely dependent on their perception of the emotional content of the task and images. We discuss implications for research on emotions in image retrieval, as well as practical implications for designers of search systems.

We present a study aimed to better understand users' perceptions of foot gestures employed on a horizontal surface. We applied a user elicitation methodology, in which participants were asked to suggest foot gestures to actions (referents) in three conditions: standing up in front of a large display, sitting down in front of a desktop display, and standing on a projected surface. Based on majority count and agreement scores, we identified three gesture sets, one for each condition. Each gesture set shows a mapping between a common action and its chosen gesture. As a further contribution, we suggest a new measure called specification score, which indicates the degree to which a gesture is specific, preferable and intuitive to an action in a specific condition of use. Finally, we present measurable insights that can be implemented as guidelines for future development and research of foot interaction.

Novel collaborative technologies afford new modes of behavior, which are often not regulated by established social norms. In particular, shared augmented reality (AR) - where multiple users can create, attach, and interact with the same virtual elements embedded into the physical environment - has the potential to interrupt current social norms of behavior. The objective of our study is to shed light on the ways in which shared AR challenges existing behavioral expectations. Using a simulated lab experimental design, we performed a study of users' interactions in a shared AR setting. Content analysis of participants' interviews reveals users' concerns over the preservation of their self- and social identity, as well as concerns related to personal space and the sense of psychological ownership over one's body and belongings. Our findings also point to the need for regulation of shared AR spaces and design of the technology's control mechanisms.

Composite Indicators (CIs), are a common measurement and benchmarking tool that are used to reflect and measure multidimensional concepts such as digital divides, individual's well-being and more. Measurement iterations produce a series of time-oriented data, which stakeholders as well as the general public might be interested to interpret. Visualization of a CI is highly recommended in order to ease interpretation, and many CI websites use radial solutions to visualize CIs. Yet it is unclear how to visualize the temporal dynamics in radial diagrams. Static solutions, mapping time to small multiples might be challenging due to screen space issues. Dynamic solutions are appealing, yet, there is no clear empirical evidence on benefits of dynamic time coding in radial diagrams. In this paper, we compare static vs. dynamic time mapping using two radial CI visualization methods. The popular Radar chart technique is compared to the innovative Flower chart as used in the well-known OECD Better Life index. We compare users' performance and preferences empirically under formal task taxonomy, adjusted to CI tasks. Results indicate that in general, static time encoding was more effective than dynamic encoding. Still, an in depth analysis showed that the dynamic approach is a feasible and sometimes even better solution for important CIs tasks, leveraged by the fact that users seem to like and enjoy it.

A promising new way of interacting with computing devices is by using our feet. Foot interaction has the potential of being an intuitive, easy to use and enjoyable way of interaction. However, there are very few guidelines for using foot interaction, or specifically foot gestures. In this research we conduct a user elicitation study for foot interaction on a horizontal surface to produce user-defined gesture sets for actions taken from two domains -- typical GUI actions and avatar controls. We analyze how foot gestures differentiate from hand gestures, point out foot gesture properties and discuss general observations.

Augmented reality (AR) technology has the potential to enrich our daily lives in many aspects. One of them is the museum visit experience. Nowadays, state of the art mobile museum visitor guides provide us with rich personalized, context aware information. However, these systems have one major drawback -- they force the visitor to hold the guide and to look at its screen. The utilization of smart-glasses technology allows providing a wearable AR display without the necessity to hold the guide and to look at it and without distracting the user from the real object. This paper describes initial steps towards the implementation of a head-worn display (HWD) museum visitor guide -- the results of users' requirements elicitation process, the implementation of a first research prototype and initial insights gathered during the process.

A composite indicator (CI) is a measuring and benchmark tool used to capture multi-dimensional concepts, such as Information and Communication Technology (ICT) usage. Individual indicators are selected and combined to reflect a phenomena being measured. Visualization of a composite indicator is recommended as a tool to enable interested stakeholders, as well as the public audience, to better understand the indicator components and evolution over time. However, existing CI visualizations introduce a variety of solutions and there is a lack in CI's visualization guidelines. Radial visualizations are popular among these solutions because of CI's inherent multi-dimensionality. Although in dispute, Radar-charts are often used for CI presentation. However, no empirical evidence on Radar's effectiveness and efficiency for common CI tasks is available. In this paper, we aim to fill this gap by reporting on a controlled experiment that compares the Radar chart technique with two other radial visualization methods: Flower-charts as used in the well-known OECD Betterlife index, and Circle-charts which could be adopted for this purpose. Examples of these charts in the current context are shown in Figure 1. We evaluated these charts, showing the same data with each of the mentioned techniques applying small multiple views for different dimensions of the data. We compared users' performance and preference empirically under a formal task-taxonomy. Results indicate that the Radar chart was the least effective and least liked, while performance of the two other options were mixed and dependent on the task. Results also showed strong preference of participants toward the Flower chart. Summarizing our results, we provide specific design guidelines for composite indicator visualization. Fig. 1: Three radial solutions for composite indicator visualizations compared empirically for users' performance and preferences.

We present a novel system for browsing through a very large set of images according to similarity. The images are dynamically placed on a 2D canvas next to their nearest neighbors in a high-dimensional feature space. The layout and choice of images is generated on-the-fly during user interaction, reflecting the user's navigation tendencies and interests. This intuitive solution for image browsing provides a continuous experience of navigating through an infinite 2D grid arranged by similarity. In contrast to common multidimensional embedding methods, our solution does not entail an upfront creation of a full global map. Image map generation is dynamic, fast and scalable, independent of the number of images in the dataset, and seamlessly supports online updates to the dataset. Thus, the technique is a viable solution for massive and constantly varying datasets consisting of millions of images. Evaluation of our approach shows that when using DynamicMaps, users viewed many more images per minute compared to a standard relevance feedback interface, suggesting that it supports more fluid and natural interaction that enables easier and faster movement in the image space. Most users preferred DynamicMaps, indicating it is more exploratory, better supports serendipitous browsing and more fun to use

Ubiquitous computing environments continuously infer our context and proactively offer us context aware services and information, suggested by notifications on our mobile devices. However, notifications come with a cost. They may interrupt the user in the current task and be annoying in the wrong context. The challenge becomes how to notify the user about the availability of relevant services while minimizing the level of disruptiveness. Thus, an understanding of what affects the subjective perception of the disruptiveness of the notification is needed. As yet, most of the research on disruptiveness of notifications focused on stationary, task-oriented environments. In this study, we examine the effect of notifications in a special leisure scenario—a museum visit. In two user studies conducted in a museum setting, participants used a context-aware mobile museum guide to receive information on various museum exhibits while periodically receiving notifications. We examined how the user’s activity, the modality of the notification, and the message content affected the perceived level of disruption that the notifications created. We discuss our results in light of existing work in the desktop and mobile domains and provide a framework and recommendations for designing notifications for a mobile museum guide system.

A plethora of tools exist for extracting and visualizing key sentiment information from a corpus of text documents. Often, however, there is a need for quickly assessing the sentiment and feelings that arise from an individual document. We describe an interactive tool that visualizes the sentiment of a specific document such as an online opinion, blog, or transcript, by visually highlighting the sentiment features while leaving the document text intact.

Abstract For museum curators it is imperative to learn, analyze, and understand the behavior patterns of the visitors in their museum. Recent developments in the field of indoor positioning systems make the acquisition and availability of visitor behavior data more attainable. However, the analysis of such data remains a challenge due to its noisiness, complexity and sheer size. The current paper applies information visualization techniques to analyze this data and make it more accessible to museum curators and personnel. We first provide a detailed description of the application domain including an analysis of the curators' information needs and a description of how a dataset on visitors' spatiotemporal behavior could be acquired. In order to address the curators' needs, we designed a visualization to encode and convey the information based on a newly adjusted visual glyph that we callTangram Diagrams. We thereby focus on the adaptability of the technique to a particular domain, rather than on the novelty aspects of the technique itself. We have evaluated our design decisions empirically, and conducted an expert study to describe the insights gained and the value of the information obtained from the visualization. The contribution of this work is twofold. First, we apply information visualization to the museum domain and discuss how it extends to general indoor spatiotemporal behavior analysis. Second, we show how a visual glyph metaphor can be applied in different ways and contexts to efficiently encode multi‐faceted information.

In this paper we investigate user performance and user behavior, related to the issue of who controls the point of view in a remote assistance scenario. We describe an experiment that examined users completing two different tasks with the aid of a remote gesturing device under two conditions: when control of the camera and gesturing point of view was in the hands of the remote helper, and when it was in the hands of the worker. Results indicate that in general, when most of the knowledge is with the helper, it is preferable to leave control in the hands of the helper. However, these results may depend on the situation and task at hand.

Abstract Large datasets of 3D objects require an intuitive way to browse and quickly explore shapes from the collection. We present a dynamic map of shapes where similar shapes are placed next to each other. Similarity between 3D models exists in a high dimensional space which cannot be accurately expressed in a two dimensional map. We solve this discrepancy by providing a local map with pan capabilities and a user interface that resembles an online experience of navigating through geographical maps. As the user navigates through the map, new shapes appear which correspond to the specific navigation tendencies and interests of the user, while maintaining a continuous browsing experience. In contrast with state of the art methods which typically reduce the search space by selecting constraints or employing relevance feedback, our method enables exploration of large sets without constraining the search space, allowing the user greater creativity and serendipity. A user study evaluation showed a strong preference of users for our method over a standard relevance feedback method.

We report a study of how dual display screens were used in classroom lectures for university-level courses across a variety of disciplines during five academic terms over a 2-year period. Our goal was to understand the pedagogical consequences of using more than a single electronic display screen to support classroom lectures. We deployed an in-house software system (MultiPresenter) in real classrooms. We examined the use of MultiPresenter by 8 university instructors who taught 15 courses with a total of 1,147 students during 13-week regular terms or 6-week summer terms. We observed classroom lectures, interviewed instructors, collected screen images and log files of MultiPresenter usage, and administered questionnaires to students about their subjective impressions. Based on these data, we analyzed how instructors used MultiPresenter in order to identify examples of how multiple display screens might best be used for educational purposes. The analysis revealed that the following practices are beneficial: the ability to keep information persistent for extended periods, the increased flexibility in where and when information is shown, capability for side-by-side comparison of full screens of information, simultaneous visibility of both overview (“roadmap”) and detailed (“content”) information, and extra space to annotate information. Possible hazards include difficulty focusing on specific information amidst a large amount of information and too much information changing too quickly without proper indication of the changes.

Many museums offer their visitors the use of a mobile guide to enhance their visit experience. Novel mobile guides have the potential to provide personalized, context-aware, rich content to museum visitors. However, they might also affect the way visitors behave and interact. While many studies have examined novel features that these guides can provide to enhance the visit experience, few have looked into the impact that a mobile guide might have on the actual behavior of the visitors. We describe a field study conducted with 403 actual museum visitors, over a period of 10 months comparing behaviors of visitors who used a mobile multimedia location-aware guide during their visit and that of visitors who did not use any electronic aid. Results indicate that visitors' behavior was altered considerably when using a mobile guide. Visitors using a mobile guide visited the museum longer and were attracted to and spent more time at exhibits where they could get information from the guide. In addition, we provide empirical evidence of the decoupling effect that a mobile guide has on pairs of visitors. Using a mobile guide caused visitors to reduce proximity and to interact less with their fellow group members. Finally, we discuss what may be done to reduce this negative social effect.

TeleAdvisor is a novel solution designed to support remote assistance tasks in many real-world scenarios. It consists of a video camera and a small projector mounted at the end of a tele-operated robotic arm. This enables a remote helper to view and interact with the workers' workspace, while controlling the point of view. It also provides the worker with a hands-free transportable device to be placed anywhere in his or her environment. Active tracking of the projection space is used in order to reliably correlate between the camera's view and the projector space.

Museums are both appealing and challenging as an environment for indoor positioning research. By nature, they are dense and rich in objects and information, and as a result they contain more information than a visitor can absorb in a time-limited visit. Many research projects have explored the potential of novel technologies to support information delivery to museum visitors. Having an accurate visitor position is a key factor in the success of such projects. In spite of numerous technologies experimented with, there is no prevailing indoor positioning technology. Each technology has its benefits as well as its limitations. In addition, museums have their own constrains when it comes to installation of sensors in their space. In the framework of the PIL project, a flexible "light weight" proximity based positioning system was developed and deployed at the Hecht museum and a general framework for indoor positioning is proposed. The inherent limitations of the basic technology are addressed by an abstract reasoning layer and by a dialog with the user.

In this paper we describe the in-progress work of the Pathlight navigation system for groups and individuals. Pathlight provides indoor navigation support in the museum using a handheld projector. We describe some of the advantages the system provides, look at some background, briefly describe some system features, and posit some open questions for further investigation.

Cultural heritage is an area that has recently drawn research attention, especially for exploring ways to harness novel mobile technologies for supporting visitors. The main benefit of these novel technologies is their ability to provide personalized, context-aware information services to their users. However, the use of context-awareness is connected to a fundamental issue of proactiveness – should the system keep the user in control all the time and only respond to user requests, or should the system take initiative and propose its services when needed? Proactiveness of mobile visitors' guides brings with it a possibility for better service to the user at the cost of taking control out of the user's hand. The amount of choice given to visitors is another key issue. With the vast amount of information available for each exhibit, adaptation of the amount of information by limiting the number of content items, could be warranted to filter the information according to the visitors needs. However, it is not clear how reducing choice in terms of the number of content items that are presented to the visitor affects visitor behavior and satisfaction. We examined these issues in a controlled user study conducted with actual museum visitors; comparing usage, behavior patterns, and attitudes of visitors using three versions of a location-aware mobile museum guide.

In this paper, we explore the practice of using a whiteboard for multiple tasks, and specifically how users employ whiteboards to smoothly transition between related sets of tasks. Our study underscores several basic, but important affordances of whiteboards that support this practice, including visual persistence, flexibility of interaction primitives, and their situated physicality. We discuss the implications of these findings for the design of large display applications.

Large classrooms have traditionally provided multiple blackboards on which an entire lecture could be visible. In recent decades, classrooms were augmented with a data projector and screen, allowing computer-generated slides to replace hand-written blackboard presentations and overhead transparencies as the medium of choice. Many lecture halls and conference rooms will soon be equipped with multiple projectors that provide large, high-resolution displays of comparable size to an old fashioned array of blackboards. The predominant presentation software, however, is still designed for a single medium-resolution projector. With the ultimate goal of designing rich presentation tools that take full advantage of increased screen resolution and real estate, we conducted an observational study to examine current practice with both traditional whiteboards and blackboards, and computer-generated slides. We identify several categories of observed usage, and highlight differences between traditional media and computer slides. We then present design guidelines for presentation software that capture the advantages of the old and the new and describe a working prototype based on those guidelines that more fully utilizes the capabilities of multiple displays.

We introduce MultiPresenter, a novel presentation system designed to work on very large display spaces (multiple displays or physically large high-resolution displays). MultiPresenter allows presenters to organize and present pre-made and dynamic presentations that take advantage of a very large display space accessed from a personal laptop. Presenters can use the extra space to provide long-term persistency of information to the audience. Our design deliberately separates content generation (authoring) from the presentation of content. We focus on supporting presentation flow and a variety of presentation styles, ranging from automated, scripted sequences of pre-made slides to highly dynamic ad-hoc, and non-linear content. By providing smooth transition between these styles, presenters can easily alter the flow of content during a presentation to adapt to an audience or to change emphasis in response to emerging interests. We describe our goals, rationale and the design process, providing a detailed description of the current version of the system, and discuss our experience using it throughout a one-semester first year computer science course.

With the advance in multispectral imaging, image fusion has emerged as a new and important research area. Many studies have examined human performance with specific fusion methods, over the individual input bands; yet few comparison studies have been conducted to examine which fusion method is preferable over another. This paper presents four different fusion methods, average, false color (FC), principal component analysis (PCA), or edge enhancement (EE), for multispectral imaging and their impact on human observers' performance. In our experiment, images with multiple targets were presented to 56 participants performing a target detection task. Quantitative measurements of participants' hit accuracy and reaction time were measured. Results yielded an overall superior performance in target detection with the false color and principal components analysis compared with the average and edge enhancement fusion methods