Computers & Graphics celebrates its golden anniversary in 2025. Motivated by this special event, this study presents a comprehensive bibliometric analysis of the journal, identifying key research trends, frequently cited authors, institutions, countries, and major citation patterns. The work retrieves data from the Web of Science (WoS) core collection and Scopus databases and utilizes bibliometric tools such as VOS viewer and bibliometrix software. We analyse the keyword evolution; co-citation networks and bibliographic coupling of the documents published in Computers & Graphics . The distribution of topics indicates increased attention to artificial intelligence–based methods, including deep learning, point cloud processing, and virtual reality, alongside established rendering and simulation techniques. Additionally, the bibliometric analysis of productive authors, institutions and countries, indicate increased publication and citation activity associated with institutions in Asian countries, especially China. Beyond broader trends, this study also highlights Computers & Graphics’ recent initiatives that emphasize transparency and reproducibility, such as the graphics replicability stamp and the special sections, which bridge academic conferences and high-quality journal publications. This study serves as a reference for researchers seeking to understand the historical trajectory, emerging trends, and evolving editorial priorities in computer graphics research.

We introduce HeadZoom, a hands-free interaction technique for navigating two-dimensional visual content using head movements. HeadZoom enables fluid zooming and panning using only real-time head tracking. It supports natural control in applications such as map exploration, radiograph inspection, and image browsing, where physical interaction is limited. We evaluated HeadZoom in a withinsubjects study comparing three interaction techniques-Static, Tilt Zoom, and Parallel Zoom-across spatial, error, and subjective metrics. Parallel Zoom significantly reduced total head movement compared to Static and Tilt modes. Users reported significantly lower perceived exertion for Parallel Zoom, confirming its suitability for prolonged or precision-based tasks. By minimizing movement demands while maintaining task effectiveness, HeadZoom advances the design of head-based 2D interaction in VR and creates new opportunities for accessible hands-free systems for image exploration.

Radiologists are trained professionals who use medical images to obtain clinically relevant information. However, little is known about visual search patterns and strategies radiologists employ during medical image analysis. Thus, there is a current need for guidelines to specify optimal visual search routines commonly used by radiologists. Identifying these features could improve radiologist training and assist radiologists in their work. Our study found that during the moments in which radiologists view chest X-ray images in silence before verbalizing the analysis, they exhibit unique search patterns regardless of the type of disease depicted. Our findings suggest that radiologists’ search behaviors can be identified at this stage. However, when radiologists verbally interpret the X-rays, the gaze patterns appear noisy and arbitrary. Current deep-learning approaches train their systems using this noisy and arbitrary gaze data. This may explain why previous research still needs to show the superiority of deep-learning models that use eye tracking for disease classification. Our paper investigates these patterns and attempts to uncover the eye-gaze configurations during the different analysis phases.

course Share on Approaches and Challenges in XR and AI for Health Applications Authors: Joaquim Jorge INESC-ID & IST, Universidade de Lisboa INESC-ID & IST, Universidade de LisboaView Profile , João Pereira INESC-ID & IST, Universidade de Lisboa INESC-ID & IST, Universidade de LisboaView Profile , Anderson Maciel INESC-ID & IST, Universidade de Lisboa INESC-ID & IST, Universidade de LisboaView Profile , Catarina Moreira Technical University Sydney Technical University SydneyView Profile , Regis Kopper UNC Greensboro UNC GreensboroView Profile Authors Info & Claims SA '23: SIGGRAPH Asia 2023 CoursesDecember 2023Article No.: 2Pages 1–147https://doi.org/10.1145/3610538.3614640Published:06 December 2023Publication History 0citation52DownloadsMetricsTotal Citations0Total Downloads52Last 12 Months52Last 6 weeks15 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

Remote collaborative work has become pervasive in many settings, ranging from engineering to medical professions. Users are im-mersed in virtual environments and communicate through life-sized avatars that enable face-to-face collaboration. Within this context, users often collaboratively view and interact with virtual 3D models, for example to assist in the design of new devices such as cus-tomized prosthetics, vehicles or buildings. Discussing such shared 3D content face-to-face, however, has a variety of challenges such as ambiguities, occlusions, and different viewpoints that all decrease mutual awareness, which in turn leads to decreased task performance and increased errors. To address this challenge, we introduce MAGIC, a novel approach for understanding pointing gestures in a face-to-face shared 3D space, improving mutual understanding and awareness. Our approach distorts the remote user's gestures to correctly reflect them in the local user's reference space when face-to-face. To measure what two users perceive in common when using pointing gestures in a shared 3D space, we introduce a novel metric called pointing agreement. Results from a user study suggest that MAGIC significantly improves pointing agreement in face-to-face collaboration settings, improving co-presence and awareness of interactions performed in the shared space. We believe that MAGIC improves remote collaboration by enabling simpler communication mechanisms and better mutual awareness.

Highly complex and dense models of 3D objects have recently become indispensable in digital industries. Mesh decimation then plays a crucial role in the production pipeline to efficiently get visually convincing yet compact expressions of complex meshes. However, the current pipeline typically does not allow artists control the decimation process, just a simplification rate. Thus a preferred approach in production settings splits the process into a first pass of saliency detection highlighting areas of greater detail, and allowing artists to iterate until satisfied before simplifying the model. We propose a novel, efficient multi-scale method to compute mesh saliency at coarse and finer scales, based on fast mesh entropy of local surface measurements. Unlike previous approaches, we ensure a robust and straightforward calculation of mesh saliency even for densely tessellated models with millions of polygons. Moreover, we introduce a new adaptive subsampling and interpolation algorithm for saliency estimation. Our implementation achieves speedups of up to three orders of magnitude over prior approaches. Experimental results showcase its resilience to problem scenarios that efficiently scales up to process multi-million vertex meshes. Our evaluation with artists in the entertainment industry also demonstrates its applicability to real use-case scenarios.

Visual analytics combines automated analysis techniques with interactive visualizations for effective understanding, reasoning, and decision-making on complex data. However, accurately classifying sentiments and stances in sentiment analysis remains challenging due to ambiguity and individual differences. This survey examines 35 papers published between 2016 and 2022, identifying unaddressed sources of friction that contribute to a gap between individual sentiment, processed data, and visual representation. We explore the impact of visualizations on data perception, analyze existing techniques, and investigate the many facets of uncertainty in sentiment and stance visualizations. We also discuss the evaluation methods used and present opportunities for future research. Our work addresses a gap in previous surveys by focusing on uncertainty and the visualization of sentiment and stance, providing valuable insights for researchers in graphical models, computational methods, and information visualization.

Monitoring and analyzing physical activity is becoming an important task in both clinical and non-clinical settings. To accomplish this desideratum, stick figures are often used as abstractions of human poses and movements by representing body segments as straight lines (sticks). Despite their straightforwardness, this minimalist representation is incomplete as it lacks the segments’ longitudinal rotations, and therefore, is insufficient for applications requiring full 3D kinematic data. We introduce STONES, an advanced machine learning approach for estimating longitudinal body segment rotations of based on stick figures defined from a minimal set of body points. Our approach relies on a recurrent deep neural network, which takes 3D joint positions from a minimalist stick figure representation, such as those acquired by conventional depth camera sensors, and completes it with accurate longitudinal segment rotations. We validated our approach via a test scenario based on exergaming activities (e.g., lunges, squats, and kicks), which are becoming an emerging trend in several healthcare sectors, and our estimations show a fit above 98% and mean errors of approximately 1 ∘. Our deep learning approach effectively surpasses other machine learning-based strategies and closely matches the accuracy of state-of-the-art motion capture systems while running at real-time speeds.

The recent pandemic, war, and oil crises have caused many to reconsider their need to travel for education, training, and meetings. Providing assistance and training remotely has thus gained importance for many applications, from industrial maintenance to surgical telemonitoring. Current solutions such as video conferencing platforms lack essential communication cues such as spatial referencing, which negatively impacts both time completion and task performance. Mixed Reality (MR) offers opportunities to improve remote assistance and training, as it opens the way to increased spatial clarity and large interaction space. We contribute a survey of remote assistance and training in MR environments through a systematic literature review to provide a deeper understanding of current approaches, benefits and challenges. We analyze 62 articles and contextualize our findings along a taxonomy based on degree of collaboration, perspective sharing, MR space symmetry, time, input and output modality, visual display, and application domain. We identify the main gaps and opportunities in this research area, such as exploring collaboration scenarios beyond one-expert-to-one-trainee, enabling users to move across the reality-virtuality spectrum during a task, or exploring advanced interaction techniques that resort to hand or eye tracking. Our survey informs and helps researchers in different domains, including maintenance, medicine, engineering, or education, build and evaluate novel MR approaches to remote training and assistance. All supplemental materials are available at https://augmented-perception.org/publications/2023-training-survey.html.

This paper summarizes the contributions to the AVI 2022 workshop on “Enhancing Cross-reality Applications and User Experiences”.

Chronic pain is a continuous ailment lasting for long periods after the initial injury or disease has healed. Chronic pain is challenging to treat and affects the daily lives of patients. Distraction therapy is a proven method of relieving patients’ discomfort by taking their attention away from the pain. Virtual reality (VR) is a platform for distraction therapy by immersing the user in a virtual world detached from reality. However, there is little research on how physical interactions in VR affect pain management. We present a study to evaluate the effectiveness of physically active, mentally active, and passive interventions in VR using games with chronic pain patients. Our results indicate that physical and mental activities in VR are equally effective at reducing pain. Furthermore, These actively engage patients, while the effects of observing relaxing content persist outside VR. These findings can help inform the design of future VR games targeted at chronic pain management.

Head-Mounted Virtual reality (VR) systems provide full-immersive experiences to users and completely isolate them from the outside world, placing them in unsafe situations. Existing research proposed different alert-based solutions to address this. Our work builds on these studies on notification systems for VR environments from a different perspective. We focus on: (i) exploring alert systems to notify VR users about non-immersed bystanders' in socially related, non-critical interaction contexts; (ii) understanding how best to provide awareness of non-immersed bystanders while maintaining presence and immersion within the Virtual Environment(VE). To this end, we developed single and combined alert cues - leveraging proxemics, perception channels, and push/pull approaches and evaluated those via two user studies. Our findings indicate a strong preference towards maintaining immersion and combining audio and visual cues, push and pull notification techniques that evolve dynamically based on proximity.

Locomotion in virtual environments is currently a difficult and unnatural task to perform. Normally, researchers tend to devise ground- or floor-based metaphors to constrain the degrees of freedom (DoFs) during motion. These restrictions enable interactions that accurately emulate the human gait to provide high interaction fidelity. However, flying allows users to reach specific locations in a virtual scene more expeditiously. Our experience suggests that even though flying is not innate to humans, high-interaction-fidelity techniques may also improve the flying experience since flying requires simultaneously controlling additional DoFs. We present the Magic Carpet, an approach to flying that combines a floor proxy with a full-body representation to avoid balance and cybersickness issues. This design space enables DoF separation by treating direction indication and speed control as two separate phases of travel, thereby enabling techniques with higher interaction fidelity. To validate our design space, we conducted two complementary studies, one for each of the travel phases. In this paper, we present the results of both studies and report the best techniques for use within the Magic Carpet design space. To this end, we use both objective and subjective measures to evaluate the efficiency, embodiment effect, and side effects, such as physical fatigue and cybersickness, of the tested techniques in our design space. Our results show that the proposed approach enables high-interaction-fidelity techniques while improving the user experience.

When engaged in communication, people often rely on pointing gestures to refer to out-of-reach content. However, observers frequently misinterpret the target of a pointing gesture. Previous research suggests that to perform a pointing gesture, people place the index finger on or close to a line connecting the eye to the referent, while observers interpret pointing gestures by extrapolating the referent using a vector defined by the arm and index finger. In this paper we present Warping Deixis, a novel approach to improving the perception of pointing gestures and facilitate communication in collaborative Extended Reality environments. By warping the virtual representation of the pointing individual, we are able to match the pointing expression to the observer's perception. We evaluated our approach in a co-located side by side virtual reality scenario. Results suggest that our approach is effective in improving the interpretation of pointing gestures in shared virtual environments.

course Share on Approaches and challenges to virtual and augmented reality in health care and rehabilitation: a short course Authors: Joaquim Jorge U Lisboa U LisboaView Profile , Pedro Campos U Lisboa U LisboaView Profile , Daniel Simões Lopes U Lisboa U LisboaView Profile Authors Info & Claims SA '19: SIGGRAPH Asia 2019 CoursesNovember 2019 Article No.: 124Pages 1–85https://doi.org/10.1145/3355047.3359418Published:17 November 2019Publication History 0citation206DownloadsMetricsTotal Citations0Total Downloads206Last 12 Months20Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

Modern volumetric projection-based telepresence approaches are capable of providing realistic full-size virtual representations of remote people. Interacting with full-size people may not be desirable due to the spatial constraints of the physical environment, application context, or display technology. However, the miniaturization of remote people is known to create an eye gaze matching problem. Eye-contact is essential to communication as it allows for people to use natural nonverbal cues and improves the sense of “being there”. In this paper we discuss the design space for interacting with volumetric representations of people and present an approach for dynamically manipulating scale, orientation and the position of holograms which guarantees eye-contact. We created a working augmented reality-based prototype and validated it with 14 participants.

Abstract Interactions within virtual environments often require manipulating 3D virtual objects. To this end, researchers have endeavoured to find efficient solutions using either traditional input devices or focusing on different input modalities, such as touch and mid‐air gestures. Different virtual environments and diverse input modalities present specific issues to control object position, orientation and scaling: traditional mouse input, for example, presents non‐trivial challenges because of the need to map between 2D input and 3D actions. While interactive surfaces enable more natural approaches, they still require smart mappings. Mid‐air gestures can be exploited to offer natural manipulations mimicking interactions with physical objects. However, these approaches often lack precision and control. All these issues and many others have been addressed in a large body of work. In this article, we survey the state‐of‐the‐art in 3D object manipulation, ranging from traditional desktop approaches to touch and mid‐air interfaces, to interact in diverse virtual environments. We propose a new taxonomy to better classify manipulation properties. Using our taxonomy, we discuss the techniques presented in the surveyed literature, highlighting trends, guidelines and open challenges, that can be useful both to future research and to developers of 3D user interfaces.

Head-Mounted Displays are useful to place users in virtual reality (VR). They do this by totally occluding the physical world, including users' bodies. This can make self-awareness problematic. Indeed, researchers have shown that users' feeling of presence and spatial awareness are highly influenced by their virtual representations, and that self-embodied representations (avatars) of their anatomy can make the experience more engaging. On the other hand, recent user studies show a penchant towards a third-person view of one's own body to seemingly improve spatial awareness. However, due to its unnaturality, we argue that a third-person perspective is not as effective or convenient as a first-person view for task execution in VR. In this paper, we investigate, through a user evaluation, how these perspectives affect task performance and embodiment, focusing on navigation tasks, namely walking while avoiding obstacles. For each perspective, we also compare three different levels of realism for users' representation, specifically a stylized abstract avatar, a mesh-based generic human, and a real-time point-cloud rendering of the users' own body. Our results show that only when a third-person perspective is coupled with a realistic representation, a similar sense of embodiment and spatial awareness is felt. In all other cases, a first-person perspective is still better suited for navigation tasks, regardless of representation.

Reading room conditions such as illumination, ambient light, human factors and display luminance, play an important role on how radiologists analyze and interpret images. Indeed, serious diagnostic errors can appear when observing images through everyday monitors. Typically, these occur whenever professionals are ill-positioned with respect to the display or visualize images under improper light and luminance conditions. In this work, we show that virtual reality can assist radiodiagnostics by considerably diminishing or cancel out the effects of unsuitable ambient conditions. Our approach combines immersive head-mounted displays with interactive surfaces to support professional radiologists in analyzing medical images and formulating diagnostics. We evaluated our prototype with two senior medical doctors and four seasoned radiology fellows. Results indicate that our approach constitutes a viable, flexible, portable and cost-efficient option to traditional radiology reading rooms.

Context-aware pervasive applications can improve user experiences by tracking people in their surroundings. Such systems use multiple sensors to gather information regarding people and devices. However, when developing novel user experiences, researchers are left to building foundation code to support multiple network-connected sensors, a major hurdle to rapidly developing and testing new ideas.

Virtual Reality environments are able to offer natural interaction metaphors. However, it is difficult to accurately place virtual objects in the desired position and orientation using gestures in mid-air. Previous research concluded that the separation of degrees-of-freedom (DOF) can lead to better results, but these benefits come with an increase in time when performing complex tasks, due to the additional number of transformations required. In this work, we assess whether custom transformation axes can be used to achieve the accuracy of DOF separation without sacrificing completion time. For this, we developed a new manipulation technique, MAiOR, which offers translation and rotation separation, supporting both 3-DOF and 1-DOF manipulations, using personalized axes for the latter. Additionally, it also has direct 6-DOF manipulation for coarse transformations, and scaled object translation for increased placement. We compared MAiOR against an exclusively 6-DOF approach and a widget-based approach with explicit DOF separation. Results show that, contrary to previous research suggestions, single DOF manipulations are not appealing to users. Instead, users favored 3-DOF manipulations above all, while keeping translation and rotation independent.

Detecting and analyzing protein cavities provides significant information about active sites for biological processes (e.g., protein-protein or protein-ligand binding) in molecular graphics and modeling. Using the three-dimensional structure of a given protein (i.e., atom types and their locations in 3D) as retrieved from a PDB (Protein Data Bank) file, it is now computationally viable to determine a description of these cavities. Such cavities correspond to pockets, clefts, invaginations, voids, tunnels, channels, and grooves on the surface of a given protein. In this work, we survey the literature on protein cavity computation and classify algorithmic approaches into three categories: evolution-based, energy-based, and geometry-based. Our survey focuses on geometric algorithms, whose taxonomy is extended to include not only sphere-, grid-, and tessellation-based methods, but also surface-based, hybrid geometric, consensus, and time-varying methods. Finally, we detail those techniques that have been customized for GPU (Graphics Processing Unit) computing.

We present an intelligent user interface that allows people to perform rehabilitation exercises by themselves under the offline supervision of a therapist. Every year, many people suffer injuries that require rehabilitation. This entails considerable time overheads since it requires people to perform specified exercises under the direct supervision of a therapist. Therefore it is desirable that patients continue performing exercises outside the clinic (for instance at home, thus without direct supervision), to complement in-clinic physical therapy. However, to perform rehabilitation tasks accurately, patients need appropriate feedback, as otherwise provided by a physical therapist, to ensure that these unsupervised exercises are correctly executed. Different approaches address this problem, providing feedback mechanisms to aid rehabilitation. Unfortunately, test subjects frequently report having trouble to completely understand the feedback thus provided, which makes it hard to correctly execute the prescribed movements. Worse, injuries may occur due to incorrect performance of the prescribed exercises, which severely hinders recovery. SleeveAR is a novel approach to provide real-time, active feedback, using multiple projection surfaces to provide effective visualizations. Empirical evaluation shows the effectiveness of our approach as compared to traditional video-based feedback. Our experimental results show that our intelligent UI can successfully guide subjects through an exercise prescribed (and demonstrated) by a physical therapist, with performance improvements between consecutive executions, a desirable goal to successful rehabilitation.

We present an interaction technique combining tactile actions and midair pointing to access out-of-reach content on large displays without the need to walk across the display. Users can start through a touch gesture on the display surface and finish midair by pointing to push content away or inversely to retrieve a content. The technique takes advantage of well-known semantics of pointing in human-to-human interaction. These, coupled with the semantics of proximal relations and deictic proxemics make the proposed technique very powerful as it leverages on well-understood human-human interaction modalities. Experimental results show this technique to outperform direct tactile interaction on dragging tasks. From our experience we derive four guidelines for interaction with large-scale displays.

Travel on Virtual Environments is the simple action where a user moves from a starting point A to a target point B. Choosing an incorrect type of technique could compromise the Virtual Reality experience and cause side effects such as spatial disorientation, fatigue and cybersickness. The design of effective travelling techniques demands to be as natural as possible, thus real walking techniques presents better results, despite their physical limitations. Approaches to surpass these limitations employ techniques that provide an indirect travel metaphor such as point-steering and target-based. In fact, target-based techniques evince a reduction in fatigue and cybersickness against the point-steering techniques, even though providing less control. In this paper we investigate further effects of speed and transition on target-based techniques on factors such as comfort and cybersickness using a Head-Mounted Display setup.

Head-Mounted Displays (HMDs) and similar 3D visualization devices are becoming ubiquitous. Going a step forward, HMD see-through systems bring virtual objects to real world settings, allowing augmented reality to be used in complex engineering scenarios. Of these, optical and video see-through systems differ on how the real world is captured by the device. To provide a seamless integration of real and virtual imagery, the absolute depth and size of both virtual and real objects should match appropriately. However, these technologies are still in their early stages, each featuring different strengths and weaknesses which affect the user experience. In this work we compare optical to video see-through systems, focusing on depth perception via exocentric and egocentric methods. Our study pairs Meta Glasses, an off-the-shelf optical see-through, to a modified Oculus Rift setup with attached video-cameras, for video see-through. Results show that, with the current hardware available, the video see-through configuration provides better overall results. These experiments and our results can help interaction designers for both virtual and augmented reality conditions.

Object manipulation is a key feature in almost every virtual environment. However, it is difficult to accurately place an object in immersive virtual environments using mid-air gestures that mimic interactions in the physical world, although being a direct and natural approach. Previous research studied mouse and touch based interfaces concluding that separation of degrees-of-freedom (DOF) led to improved results. In this paper, we present the first user evaluation to assess the impact of explicit 6 DOF separation in mid-air manipulation tasks. We implemented a technique based on familiar virtual widgets that allow single DOF control, and compared it against a direct approach and PRISM, which dynamically adjusts the ratio between hand and object motions. Our results suggest that full DOF separation benefits precision in spatial manipulations, at the cost of additional time for complex tasks. From our results we draw guidelines for 3D object manipulation in mid-air.

Physiotherapy patients exercising at home alone are at risk of re-injury since they do not have corrective guidance from a therapist. To explore solutions to this problem, we designed Physio@Home, a prototype that guides people through prerecorded physiotherapy exercises using real-time visual guides and multi-camera views. Our design addresses several aspects of corrective guidance, including: plane and range of movement, joint positions and angles, and extent of movement. We evaluated our design, com-paring how closely people could follow exercise movements under various feedback conditions. Participants were most accurate when using our visual guide and multi-views. We provide suggestions for exercise guidance systems drawn from qualitative findings on visual feedback complexity.

Transparent displays can serve as an important collaborative medium supporting face-to-face interactions over a shared visual work surface. Such displays enhance workspace awareness: when a person is working on one side of a transparent display, the person on the other side can see the other's body, hand gestures, gaze and what he or she is actually manipulating on the shared screen. Even so, we argue that designing such transparent displays must go beyond current offerings if it is to support collaboration. First, both sides of the display must accept interactive input, preferably by at least touch and / or pen, as that affords the ability for either person to directly interact with the workspace items. Second, and more controversially, both sides of the display must be able to present different content, albeit selectively. Third (and related to the second point), because screen contents and lighting can partially obscure what can be seen through the surface, the display should visually enhance the actions of the person on the other side to better support workspace awareness. We describe our prototype FACINGBOARD-2 system, where we concentrate on how its design supports these three collaborative requirements.

Large-scale touch surfaces have been widely studied in literature and adopted for public installations such as interactive billboards. However, current designs do not take into consideration that touching the interactive surface at different heights is not the same; for body-height displays, the bottom portion of the screen is within easier reach of the foot than the hand. We explore the design space of foot input on vertical surfaces, and propose three distinct interaction modalities: hand, foot tapping, and foot gesturing. Our design exploration pays particular attention to areas of the touch surface that were previously overlooked: out of hand's reach and close to the floor. We instantiate our design space with a working prototype of an interactive surface, in which we are able to distinguish between finger and foot tapping and extend the input area beyond the bottom of the display to support foot gestures.

This paper describes the results of a pedagogical experiment using an Intelligent Tutoring System that also implements an Animated Pedagogical Agent. The study was performed in Portugal, as an attempt to replicate some experiments performed in the USA, and in order to verify the usefulness of the Pedagogical Agent in a different country with distinct culture. After running the experiment and analyzing the data, we have concluded that in our specific case, we did not find any evidence that the pedagogical agent could boost instructional outcomes of students in Portugal. Our data is showing no statistically significant differences between the control, and experimental groups. Additionally, we have also found that the control group actually performed slightly better than the experimental group. As a result, our study is giving some good evidences that a Pedagogical Agent that was developed, tested and successfully used in one country, may not be successful when used in a different country.

Due to interoperability issues, Intelligent Tutoring Systems are hard to deploy in the different educational platforms available nowadays. This represents a considerable limitation, since tutoring systems require substantial time and a lot of resources to be implemented. This paper describes a new architecture for developing open source and interoperable intelligent tutors. In our approach, "atomic" tutoring systems are grouped to create "molecular" tree structures covering the curriculum of courses. Based on standards, our approach provides interoperable and open source ITSs that can be retrieved from repositories of educational content, grouped when necessary, loaded into different educational platforms and have their code reused for incremental development.

Touchscreen devices have become increasingly popular. Yet they lack of tactile feedback and motor stability, making it difficult effectively typing on virtual keyboards. This is even worse for elderly users and their declining motor abilities, particularly hand tremor. In this paper we examine text-entry performance and typing patterns of elderly users on touch-based devices. Moreover, we analyze users' hand tremor profile and its relationship to typing behavior. Our main goal is to inform future designs of touchscreen keyboards for elderly people. To this end, we asked 15 users to enter text under two device conditions (mobile and tablet) and measured their performance, both speed- and accuracy-wise. Additionally, we thoroughly analyze different types of errors (insertions, substitutions, and omissions) looking at touch input features and their main causes. Results show that omissions are the most common error type, mainly due to cognitive errors, followed by substitutions and insertions. While tablet devices can compensate for about 9% of typing errors, omissions are similar across conditions. Measured hand tremor largely correlates with text-entry errors, suggesting that it should be approached to improve input accuracy. Finally, we assess the effect of simple touch models and provide implications to design.

Mobile touch devices have become increasingly popular, yet typing on virtual keyboards whilst walking is still an overwhelming task. In this paper we analyze; firstly, the negative effect of walking on text-input performance, particularly the users' main difficulties and error patterns. We focused our research on thumb typing, since this is a commonly used technique to interact with touch interfaces. Secondly, we analyze how these effects can be compensated by two-hand interaction and increasing target size. We asked 22 participants to input text under three mobility conditions (seated, slow walking, and normal walking) and three hand conditions (one-hand/portrait, two-hand/portrait, and two-hand/landscape). Results show that independently of hand condition, mobility significantly decreased input quality, leading to specific error patterns. Moreover, it was shown that target size can compensate the negative effect of walking, while two-hand interaction does not provide additional stability or input accuracy. We finish with implications for future designs.

The growing number of three-dimensional (3D) objects stored in digital libraries brought forth the challenge of search in 3D model collections. To address it, several approaches have been developed for 3D object retrieval. However, these approaches traditionally present query results as a list of thumbnails, and fail to take advantage of recent visualization and interaction technologies. In this paper, we propose an approach to 3D object retrieval using immersive VR for query result visualization. Query results are shown in a three-dimensional virtual space as 3D objects and users can explore these results by navigating in this virtual space and manipulating the scattered objects.

Immersive 3D Virtual Environments (VE) have become affordable for many research centers. However, a complete solution needs several integration steps to be fully operational. Some of these steps are difficult to accomplish and require an uncommon combination of different skills. This tutorial presents the most recent techniques developed to address this problem, from displays to software tools. The hardware in a typical VR installations combines projectors, screens, speakers, computers, tracking and I/O devices. The tutorial will discuss hardware options, explaining their advantages and disadvantages. We will cover design decisions from basic software and hardware design, through user tracking, multimodal human-computer interfaces and acoustic rendering, to how to administrate the whole solution. Additionally, we will provide an introduction to existing tracking technologies, explaining how the most common devices work, while focusing on infrared optical tracking. Finally, we briefly cover integration software and middleware developed for most VE settings.

The emergence of touch-based mobile devices brought fresh and exciting possibilities. These came at the cost of a considerable number of novel challenges. They are particularly apparent with the blind population, as these devices lack tactile cues and are extremely visually demanding. Existing solutions resort to assistive screen reading software to compensate the lack of sight, still not all the information reaches the blind user. Good spatial ability is still required to have notion of the device and its interface, as well as the need to memorize buttons' position on screen. These abilities, as many other individual attributes as age, age of blindness onset or tactile sensibility are often forgotten, as the blind population is presented with the same methods ignoring capabilities and needs. Herein, we present a study with 13 blind people consisting of a touch screen text-entry task with four different methods. Results show that different capability levels have significant impact on performance and that this impact is related with the different methods' demands. These variances acknowledge the need of accounting for individual characteristics and giving space for difference, towards inclusive design.

The rising popularity of digital table surfaces has spawned considerable interest in new interaction techniques. Most interactions fall into one of two modalities: 1) direct touch and multi-touch (by hand and by tangibles) directly on the surface, and 2) hand gestures above the surface. The limitation is that these two modalities ignore the rich interaction space between them. To move beyond this limitation, we first contribute a unification of these discrete interaction modalities called the continuous interaction space . The idea is that many interaction techniques can be developed that go beyond these two modalities, where they can leverage the space between them. That is, we believe that the underlying system should treat the space on and above the surface as a continuum , where a person can use touch, gestures, and tangibles anywhere in the space and naturally move between them. Our second contribution illustrates this, where we introduce a variety of interaction categories that exploit the space between these modalities. For example, with our Extended Continuous Gestures category, a person can start an interaction with a direct touch and drag, then naturally lift off the surface and continue their drag with a hand gesture over the surface. For each interaction category, we implement an example (or use prior work) that illustrates how that technique can be applied. In summary, our primary contribution is to broaden the design space of interaction techniques for digital surfaces, where we populate the continuous interaction space both with concepts and examples that emerge from considering this space as a continuum.

Touch screen mobile devices bear the promise of endless leisure, communication, and productivity opportunities to motor-impaired people. Indeed, users with residual capacities in their upper extremities could benefit immensely from a device with no demands regarding strength. However, the precision required to effectively select a target without physical cues creates problems to people with limited motor abilities. Our goal is to thoroughly study mobile touch screen interfaces, their characteristics and parameterizations, thus providing the tools for informed interface design for motor-impaired users. We present an evaluation performed with 15 tetraplegic people that allowed us to understand the factors limiting user performance within a comprehensive set of interaction techniques (Tapping, Crossing, Exiting and Directional Gesturing) and parameterizations (Position, Size and Direction). Our results show that for each technique, accuracy and precision vary across different areas of the screen and directions, in a way that is directly dependent on target size. Overall, Tapping was both the preferred technique and among the most effective. This proves that it is possible to design inclusive unified interfaces for motor-impaired and able-bodied users once the correct parameterization or adaptability is assured.

Mobile touch-screen interfaces and tetraplegic people have a controversial connection. While users with residual capacities in their upper extremities could benefit immensely from a device which does not require strength to operate, the precision needed to effectively select a target bars these people access to countless communication, leisure and productivity opportunities. Insightful projects attempted to bridge this gap via either special hardware or particular interface tweaks. Still, we need further insight into the challenges and the frontiers separating failure from success for such applications to take hold. This paper discusses an evaluation conducted with 15 tetraplegic people to learn the limits to their performance within a comprehensive set of interaction methods. We then present the results concerning a particular interaction technique: Tapping. Results show that performance varies across different areas of the screen whose distribution changes with target size.

We are moving towards a future where people will be ever more surrounded by technology and multiple appliances, bringing about the promise of truly intelligent environments. However, this multitude of devices raises several issues to HCI practitioners. Indeed, our preliminary studies confirm that blind people experience difficulties with most appliances, due to inadequate interfaces. The research described here approaches this problem by moving the user interface away from appliances to an intermediary device, which blind people are familiar with and can fully control. Additionally, we propose an automatic generation algorithm, which provides a consistent user interface to all appliances in the environment.

NavTap is a navigational method that enables blind users to input text in a mobile device by reducing the associated cognitive load.

With the growing popularity of digital cameras, the organization, browsing, management and grouping of photos become a problem of every photograph (professional or amateur), because their collections easily achieve the order of thousands. Here, we present a system to automate these processes, which relies on photo information, such as, semantic features (extracted from content), meta-information and low level.

Most computer users find organizing large amounts of personal information problematic. Often, hierarchies are the sole means to do it. However, users can remember a broader range of autobiographic contextual data about their personal items. Unfortunately, it can seldom be used to manage and retrieve them. Even when this is possible, it is often done by asking users to fill in values for arbitrary properties in dialog boxes or wizards.

Summary form only given. CAD systems now enable us to manufacture complicated models. However, computers have yet to become usable at the very early stages of product design, where pencil and paper still reign. This is because present-day systems, with their focus on internal representation and dialogue hierarchies, require designers to leap large conceptual gaps when evolving from their idea of a desired object to the geometric model that formally expresses its intended shape. As computers become more sophisticated and powerful, alternative input modalities and interface techniques are emerging which form the basis for a new generation of sketching applications supporting what we call Calligraphic interfaces, where artificial dialogue constraints imposed by the previous generation of UIs are removed. We are exploring with minimalist approaches and techniques to approximate traditional methods including modeling, illustration and retrieval. I will talk about our research and ongoing projects at the Technical University of Lisbon, towards this goal.

We present a framework to manage multimodal applications and interfaces in a reusable and extensible manner. We achieve this by focusing the architecture both on applications' needs and devices' capabilities. One particular domain we want to approach is collaborative environments where several modalities and applications make it necessary to provide for an extensible system combining diverse components across heterogeneous platforms on-the-fly. This paper describes the proposed framework and its main contributions in the context of an architectural application scenario. We demonstrate how to connect different non-conventional applications and input modalities around an immersive environment (tiled display wall).

Traditional ways to help users organize and retrieve their documents don't scale well, nor do they properly handle non-textual documents. This paper evaluates narrative-based interfaces as a natural and effective alternative for document retrieval. We have identified what shape document-describing stories take, and what contents to expect. This led to an interface that is able to capture stories, and a knowledge-based infrastructure to understand them. A prototype of the interface was used to validate narrative-based interfaces, with emphasis on story accuracy. To this end, we collected thirty stories whose contents were then compared to the documents they portrayed. Results allow us to conclude that, for the most part, such stories are trustworthy enough to allow humans to retrieve documents reliably (81%-91% of all information is correct). We also confirmed that stories told to a computer are similar to those told to human interviewers.

to present a challenge in terms of performance, robustness and accuracy. In particular mobile augmented reality applications are in need of tracking systems which can be wearable and do not cause a high processing load. In this paper we introduce a novel iterative geometric method for pose estimation from four co-planar points and we present the current status of PTrack, a marker-based single camera tracking system benefiting from this approach. The system uses an IDS uEye [1] camera, equipped with infrared flash strobes and infrared pass filter, which acquires grayscale images and sends them to a computer where an image pre-processing algorithm identifies potential projections of retro-reflective markers. Our novel pose estimation algorithm identifies possible labels composed of markers in a 2D post-processing using a divide-and-conquer strategy to segment the camera's image space and attempts an iterative geometric 3D reconstruction of position and orientation in camera space. In the end successfully reconstructed labels are compared to a database for identification. Their 6 DoF data as well as their ID is made available to applications through OpenTracker [2] framework. To assess the performance of our approach we compared PTrack to ARToolKit [3] - which has been adapted to work with the same camera - and final results show that pose estimation is more accurate and precise, in both translation and rotation.

We present new techniques for rendering hierarchical, skeletal implicit models in several pen-and-ink styles. Our approach extracts silhouette strokes and lines following local shape features, such as those caused by CSG junc-tions. To this end, it uses particle systems to find interesting areas on the surface and perform stroke stylization guided by local shape features. Also, it removes hidden lines either by applying a surfel technique for rapid proto-typing, or more accurately by using ray tracing. Examples from simple to complex models illustrate the capabilities of our system.

These days there are a lot of vector drawings available for people to integrate into documents. These come in a variety of formats, such as Corel, Postscript, CGM, WMF and recently SVG. Typically, such ClipArt drawings tend to be archieved and accessed by categories (e.g. food, shapes, transportation, etc.). However, to find a drawing among hundreds of thousands is not an easy task. While text-driven attempts at classifying image data have been recently supplemented with query-by-image content, these have been developed for bitmap-type data and cannot handle vectorial information. In this paper we present an approach to allow indexing and retrieving vector drawings by content from large datasets. Our prototype can already handle databases with thousands of drawings using commodity hardware. Furthermore, preliminary usability assessments show promising results and suggest good acceptance of sketching as a query mechanism by users.

With the increasing number of computers per user, it has become common for most users to deal with growing numbers of electronic documents. Those documents are usually stored in hierarchic file systems, requiring them to be classified into the hierarchy, a difficult task. Such organization schemes do not provide adequate support for the efficient and effortless retrieval of documents at a later time, since their position in the hierarchy is one of the only clues to a document's whereabouts. However, humans are natural-born storytellers, and stories help relate and remember important pieces of information. Hence, the usage of narratives where a user "tells a story" about the document will be a valuable tool towards simplifying the retrieval task.To find out if there are common patterns in stories about documents, we performed a study where 60 such stories were collected and analyzed. We identified the most common story elements (time, storage and purpose) and how they are likely to relate in typical stories. This preliminary study suggests that it is possible to infer archetypical stories. Further, we present a set of guidelines for the design of narrative-based document retrieval interfaces.

Many indexing approaches for high-dimensional data points have evolved into very complex and hard to code algorithms. Sometimes this complexity is not matched by increase in performance. Motivated by these ideas, we take a step back and look at simpler approaches to indexing multimedia data. In this paper we propose a simple, (not simplistic) yet efficient indexing structure for high-dimensional data Points of variable dimension, using dimension reduction. Our approach maps multidimensional points to a 1D line by computing their Euclidean Norm and use a B/sup +/-Tree to store data points. We exploit B/sup +/-Tree efficient sequential search to develop simple, yet performant methods to implement point, range and nearest-neighbor queries. To evaluate our technique we conducted a set of experiments, using both synthetic and real data. We analyze creation, insertion and query times as a function of data set size and dimension. Results so far show that our simple scheme outperforms current approaches, such as the Pyramid Technique, the A-Tree and the SR-Tree, for many data distributions. Moreover, our approach seems to scale better both with growing dimensionality and data set size, while exhibiting low insertion and search times.

Presents a simple method, based on fuzzy logic, to recognize multi-stroke sketches of geometric shapes and uni-stroke gestural commands. It uses temporal adjacency and global geometric properties of figures to recognize a simple vocabulary of geometric shapes drawn in different line styles. The geometric features used (convex hull, largest-area inscribed and smallest-area enclosing polygons, perimeter and area ratios) are invariant with rotation and scale of figures. Through experimental evaluation we have found the method very usable with acceptable recognition rates although the multi-stroke approach poses problems in choosing appropriate values for timeouts. Although we have privileged simplicity over robustness, the method has proved suitable for interactive applications.

The authors analyze two intertwined and fundamental issues concerning computer-to-human communication in the multimodal interface; the interplay between sound and graphics, and the role of object persistence. The observations lead to metawidgets as abstract entities capable of manifesting themselves to users as image, as sound, or as various combinations and/or sequences of the two media. The authors show examples of metawidgets in action and discuss mechanisms for choosing among alternative media for metawidget instantiation. Two experimental microworlds implemented to explore these ideas are described.>