Stroke is one of the world’s leading causes of death and disability and can have profound consequences that require effective rehabilitation to support survivors’ recovery and improve their quality of life. Despite their value, traditional rehabilitation methods tend to be repetitive and lack variety, which challenges survivors’ motivation. Additionally, these rehabilitation sessions are usually solitary, leaving survivors to practice exercises alone, which can lead to physical setbacks and social isolation. Such isolation can further reduce enthusiasm for therapy, delay recovery, and affect their mental well-being. This work details an extended version from the International Workshop on eXtended Reality for Industrial and Occupational Supports (XRIOS), conducted at IEEE VR 2025. It proposes a collaborative Virtual Reality (VR) framework that aims to increase survivors’ motivation during rehabilitation. Through its collaborative nature, it can involve multiple users in the same virtual space, from stroke survivors to healthcare professionals, giving them a common goal that they must join forces to accomplish. Various serious games were designed through a series of activities focused on specific gestures related to the rehabilitation of the upper limbs, thus improving physical recovery and mental well-being. The design and development were guided by a human-centered methodology that included survivors and professionals, resulting in a user study with a total of 53 participants, 18 from a rehabilitation center. The results indicate that this collaborative VR tool effectively boosts motivation, social interaction, and engagement while maintaining an accessible and manageable level of physical and mental demand for stroke recovery, underscoring its suitability for stroke recovery.

Stroke affects millions of people worldwide, often resulting in severe physical and cognitive limitations that impact daily life. Rehabilitation is essential for improving stroke survivors' quality of life, yet traditional methods face significant limitations, including repetitive exercises, lack of personalization, and minimal social interaction. These constraints can lead to disengagement, isolation, and even depression, ultimately hindering recovery. To address these challenges, we propose ADAPT, a framework that enables healthcare professionals to personalize collaborative Virtual Reality (VR) serious games for stroke rehabilitation. It is possible to tailor rehabilitation sessions by adjusting key parameters, such as the number of participants, game selection and sequencing, session durations, and goal difficulty. Additionally, the system can incorporate familiar objects and locations to enhance emotional engagement. Realtime monitoring features provide these professionals with live streaming, adjustable viewpoints, and interactive assistance tools, ensuring continuous support and adaptation. Furthermore, data is collected and stored for performance analysis, enabling datadriven decision-making for future sessions. Developed through a Human-Centered Design (HCD) approach in collaboration with a renowned rehabilitation center in Portugal, the framework ensures usability and relevance in clinical practice. Initial testing has demonstrated positive results, with healthcare professionals praising the personalization capabilities and providing valuable feedback for further improvements. By integrating adaptive, collaborative, and engaging VR experiences, this framework aims to enhance stroke rehabilitation outcomes, increase survivors motivation, and foster social interaction, making rehabilitation more effective and personalized.

Collaborative Virtual Reality (VR) can be a powerful tool for enhancing the engagement, motivation, and social interaction of stroke survivors, significantly improving their quality of life and willingness to participate in the rehabilitation process. To ensure the success of these experiences, the active involvement of healthcare professionals is crucial, enabling them to better understand social dynamics and support stroke survivors' over time. Regardless, literature highlights a significant lack of tools to assist healthcare professionals in effectively monitoring and supporting such activities, particularly in ecological settings like rehabilitation centers. This work proposes REVIVE, a collaborative VR monitoring tool designed to enhance healthcare professionals' ability to oversee and adjust rehabilitation activities. The tool includes features such as live video streaming with adjustable perspectives, interactive annotations (e.g., directional arrows, drawings, text messages), and a virtual laser pointer. It also provides access to key session metrics and historical data, enabling professionals to tailor interventions and better understand the collaborative process of stroke survivors. Additionally, insights from two user studies are reported, involving over 60 participants, demonstrating REVIVE's potential to assist survivors, while improving how healthcare professionals manage and monitor rehabilitation involving collaborative VR scenarios.

Deep reinforcement learning is a dynamic field that has been successfully applied in various engineering and scientific disciplines. However, like many areas of automated learning, it presents a significant challenge: understanding its models, which can hinder human trust in the decisions made by these algorithms. To address this issue, we conducted a focus group and interviews with experts in machine learning and reinforcement learning to gain insights into the perceptions and preferences surrounding interpretability techniques and tools in reinforcement learning systems. The discussion of the focus groups used an interactive dashboard to simplify the analysis of reinforcement learning environments. The focus group results showed many problems to tackle with the current approaches regarding RL agent training, like data manipulation, environment representation and reward misinterpretation. The focus group discussion also presented some key features of a visualization approach to interpretability in RL: contextual presentation of information, integration with existing pipelines, and ease of distribution.

Situated visualisation (SV), which embeds data representations directly within the context to which they refer, offers a paradigm for augmenting perception, understanding, and decision-making in real-world environments. Inspired by comic-books and previous work on visualisation, this article presents the relevance of SV in the form of superpowers. Each superpower is explained through the lens of augmented reality (AR). By mapping these capabilities, the article positions SV not just as a technical advancement, but as a new frontier in human-centred design, inviting researchers to rethink the role of visualisation in a world where data and reality increasingly coexist. Therefore, the paper also offers guidelines for its effective design and implementation. Finally, a structured evaluation questionnaire (the VIEWUS), specifically designed for AR-based Situated visualisation systems, is proposed. VIEWUS integrates key factors such as usability, engagement, situational awareness, visual fatigue, and workload, combining and adapting items from established instruments. It allows for a comprehensive assessment using a 5-point Likert scale and supports iterative improvement of SV systems based on user feedback.

This work explored the impact of expert representation during the (re)use of Augmented Reality (AR) instructions for remote assistance.A user study with sixteen participants compared three conditions: C1-no agent, C2-human agent, and C3-virtual agent, within a real-world maintenance scenario.Results indicate that reusing AR-instructions was well accepted, even when not perfectly aligned with the task context.While C2 reported higher levels of social presence and trust, C3 was considered the best option when reusable content was used and limited interaction was required.This allowed to focus more on the task and less on the agent representation.

Abstract Remote collaboration using eXtended Reality (XR) has been explored to establish a common ground between physically distributed individuals. To achieve usable and impactful solutions, it is paramount to understand how different content creation and display methods contribute to the work effort of each member (remote and on-site). Additionally, explore how various task scenarios influence the collaborative process, specifically examining how activities with unique characteristics and complexities affect remote work. Hence, the question arises, ’How do different display and interaction methods impact the collaborative process within specific task domains?’ In this paper, two user studies with 30 distinct participants each are described, focusing on different content creation support (Laptop Computer; Video Wall & Keyboard; Interactive Projector) and display methods (Hand-Held Device (HHD); HHD & Articulated Support; Head-Mounted Display (HMD)) for remote and on-site collaborators respectively, during scenarios of remote guidance. Plus, different physical tasks were considered for each study (Lego pieces assembly; Tangram puzzle assembly; Maintenance procedures; Resource management in a map; Training activity in a laboratory classroom), to understand which method stands out according to the characteristics of the said tasks. We report the results obtained, suggesting that for the remote part of the collaborative process, using a Video Wall & Keyboard appears to be more suitable for tasks associated with maintenance procedures, learning, and training activities. As for the on-site part, using HMD was considered the better option for maintenance, and learning tasks, closely followed by HHD & Articulated Support.

Inspection tasks in Industry 4.0 are crucial for ensuring product quality and operational efficiency. Yet human technicians often encounter challenges due to the complexity of modern machinery, the vast amount of data to be processed, and the need for rapid decision-making. These challenges underscore the necessity for innovative solutions that can provide technicians with enhanced data visualization and intuitive guidance. This work proposes a prototype using Pervasive Augmented Reality (AR) and Situated Visualization (SV) to support inspection procedures in industrial settings. This was created in collaboration with industrial partners following a Human-Centered Design (HCD) methodology. This process allowed to identify stakeholders' needs, and challenges, as well as define requirements to guide the development of the prototype. First impressions collected in laboratory environment are described, which helped improve an initial version of the prototype. Subsequently, a user study was conducted at the shop floor environment to evaluate usability, interaction, accuracy and acceptance, as well as collect feedback on how it can be improved to better support such context.

This paper presents an Augmented Reality (AR) application based on Situated Visualization (SV), aimed at increasing awareness of air pollution. Given that technological progress must be achieved through meticulous evaluation processes, the article also presents the assessment of the stated application. Therefore, this article begins by examining how AR applications are appraised. Building upon this review, and focusing particularly on those where SV is provided, a discussion is presented regarding the points that must be carefully considered when evaluating this type of AR application, as well as the factors that need to be measured, along with the most popular methods for evaluating these factors. However, it is noted that if a simultaneous evaluation of all the factors that matter to SV is intended, the number of questions to be asked could be significant. Therefore, a preliminary approach to enable such an appraisal is proposed and used in the mentioned application to demonstrate the merits of the proposed Questionnaire.

The use of Pervasive Augmented Reality (AR) in industrial settings, particularly in the context of Industry 4.0, is a growing area of research. Industry 4.0 is characterized by the integration of advanced technologies, including AR, to enable smart, connected, and autonomous systems in manufacturing and other industries. This study focuses on two systems that use Pervasive AR for logistics and data monitoring on assembly lines. Such systems were designed using cooperative Human-Centered Design (HCD) methodologies in collaboration with partners from the industry sector. We report lessons learned and guidelines on the development of AR systems for industrial environments. In addition, a user study based on a data monitoring laboratory realistic procedure with 8 participants is described. The study compares the usability and effectiveness of a dashboard on Pervasive AR and a web tablet. Overall, results emphasize that AR was better suited when requiring spatial awareness and interventions, while traditional web tablet was better for tasks that require more interaction with the content and faster data monitoring. These findings had implications for the design of industrial tools, such as prototype improvements and idealize new methods, which can guide future efforts to develop and deploy AR applications.

Augmented Reality (AR) is a key technology in the transition to Industry 4.0 and smart manufacturing, gaining reputation in a wide range of industrial fields One promising application is in another field of Industry 4.0, the data monitoring, where AR can be used to visualize and interact with complex and big data in real time, potentially improving the efficiency and accuracy of decision-making In this work, we propose a Pervasive AR tool for data monitoring, developed in collaboration with industry partners. An web application of the same data monitoring function is also created for comparison purposes A Human-Centered Design (HCD) methodology was used to identify the needs and requirements of industrial analysts, which led to the development of these systems Preliminary user studies, with 17 participants having distinct levels of expertise in industry, data analysis and computer science, were conducted to collect opinions and suggestions for improvements, as well as, quantitative data regarding the technologies considered A succeeding user study was then prepared, in which 12 participants used two conditions (C1 - Hands-free Pervasive AR tool for HMDs and C2 - Web tool for tablet devices) to fulfill a set of data monitoring tasks in an industry assembly line The result of these studies confirm the potential of Pervasive AR for data monitoring, as it engages users, promote environmental awareness, contextualizes data and allows fast self-localization.

In recent years, the market has seen the emergence of numerous affordable sensors, interaction devices, and displays, which have greatly facilitated the adoption of Virtual and Augmented Reality (VR/AR) across various applications. However, developing these applications requires a solid understanding of the field and specific technical skills, which are often lacking in current Computer Science and Engineering education programs. This work details an extended version from a Eurographics 2024 Education Paper, reporting a post-graduate-level course that has been taught for the past ten years to almost 200 students, across several Master’s programs. The course introduces students to the fundamental principles, methods, and tools of VR/AR. Its primary objective is to equip students with the knowledge necessary to understand, create, implement, and evaluate applications using these technologies. The paper provides insights into the course structure, key topics covered, assessment methods, as well as the devices and infrastructure utilized. It also includes an overview of various practical projects completed over the years. Among other reflections, we discuss the challenges of teaching this course, particularly due to the rapid evolution of the field, which necessitates constant updates to the curriculum. Finally, future perspectives for the course are outlined. • Description of main features of a VR/AR course attended by almost two hundred students. • illustration of course structure, key topics, assessment methods, devices and infrastructure utilized. • overview of various practical VR/AR projects completed over the years. • reflection on challenges of the past ten years of teaching the VR/AR course. • presentation of future perspectives for a VR/AR course.

Augmented Reality (AR) has the ability to display and interact with additional information aligned with the real world and to support context-driven visualization techniques. Situated Visualization (SV) is a method to represent data in a context that encompasses all the visualizations that change their appearance based on context. Therefore, since AR is typically used so that the user can visualize extra information regarding the surrounding real world environment, this technology is well suited for SV and presents high potential in many situations, as are the cases of collaborative/assistive tasks in the maintenance area and supporting decision-making. AR-based visualizations are commonly constrained to the users' unique egocentric view-point, which reduces their ability to explore all the richness of available information. This limitation is particularly evident in situations that require overviews of all information inside and out of the user's field of view (FOV). This article proposes multi-perspective renderings, transitional interfaces, and the use of multimodal information as methods to extend the user's egocentric viewpoint. The main idea is to coherently present and augment, in the same user's display, dynamic and static feeds of several real and virtual egocentric viewpoints, related to and relevant for the user's task.

This work proposed the use of 3D Reconstruction, Virtual Reality (VR), and a Large Display to enhance the education process of geosciences at the university level. This approach enables teachers to immerse themselves and interact with 3D virtual replicas of real-world locations. In turn, this is cast to a projector, allowing them to better explain specific concepts to an audience of students, which can acquire new knowledge and gain a deeper understanding. A user study was conducted with 20 participants (from geosciences and computer science engineering) to evaluate this proposal versus a traditional static image approach. We report the results obtained, suggesting the VR condition represents the predominant condition for a set of dimensions considered relevant for the tasks defined.

Most efforts on Augmented Reality (AR) remote collaboration have been devoted to on-site individuals in need of assistance. Yet, since remote experts do not have access to the local environment, it is also important to explore how different methods affect the situation understanding and interaction. This work describes a user study with 16 participants aimed at comparing how remote individuals interact with standard (C1) and large-scale displays (C2) while providing assistance during a remote maintenance scenario. Results suggest condition C2 was preferred by the majority of participants, being considered more useful to analyze important details of the task context, as well as more easily create content.

Situated Visualization (SV), encompassing all the visualizations that change their appearance based on context, by considering the visualizations that are relevant to the physical context in which they are displayed [1], has been recognized as a method with potential in many situations, as is the case of supporting decision making [2]. Augmented and Mixed Reality (AR/MR) are well suited to assist in such scenarios, given its ability to display additional data regarding the real-world context and be supported by context-driven visualization techniques [3]. Though some perspectives on the SV model have been proposed, such as space, time, place, activity and community, an appropriate systematization, covering the main definitions and perspectives has yet to be established. Hence, there is an urge to obtain a more comprehensive description. The work presented in this paper characterizes the SV model, within the scope of AR/MR, shows a critical analysis of the existing knowledge, expanding the SV model and in turn hoping to elicit discussion within the research community.

Pervasive Augmented Reality (AR) has been explored to provide experiences that are continuous in space and time, while incorporating layers of contextual information. While most research efforts have been devoted to explore serious games, museums and smart environments, we argue that another interesting area of application is assistive production, in particular training novel workers by displaying instructions throughout the shop floor on what to do. This work describes a user study with 12 participants, aimed at comparing the use of three distinct conditions: C1 - Head-Mounted Display (HMD), C2 - Handheld Device (HHD) and C3 - Paper manual during a set of realistic training tasks, selected based on a collaboration with partners from the industry sector. Results suggest condition C1 was preferred by the majority of participants, being considered more useful to support the worker’s task as it is seems more efficient, hands-free and has a better tracking technology.

Although Mixed Reality (MR) has been explored to support scenarios of remote collaboration, the majority of studies reported in literature have focused on synchronous use-cases, where all team-members can interact in real-time. Hence, an opportunity exist to explore asynchronous situations, in which collaborative actions take place at different times. Despite the physical distance and different time zones, remote experts can generate MR-instructions to assist with emerging problems, suggesting to on-site collaborators where to act, and what to do. This work explored three distinct notification methods for such scenarios: C1 - visual cue; C2 - audio cue; C3 - tactile cue, aiming to comprehend which one captures the attention of on-site team-members easily. A user study with 12 participants was conducted to evaluate these conditions during an asynchronous scenario of remote maintenance. We report participants insights, suggesting tactile cues represent the predominant condition given the scenario context.

To support the nuances of collaborative work, many researchers have been exploring the field of Augmented Reality (AR), aiming to assist in co-located or remote scenarios. Solutions using AR allow taking advantage from seamless integration of virtual objects and real-world objects, thus providing collaborators with a shared understanding or common ground environment. However, most of the research efforts, so far, have been devoted to experiment with technology and mature methods to support its design and development. Therefore, it is now time to understand where the field stands and how well can it address collaborative work with AR, to better characterize and evaluate the collaboration process. In this article, we perform an analysis of the different dimensions that should be taken into account when analysing the contributions of AR to the collaborative work effort. Then, we bring these dimensions forward into a conceptual framework and propose an extended human-centered taxonomy for the categorization of the main features of Collaborative AR. Our goal is to foster harmonization of perspectives for the field, which may help create a common ground for systematization and discussion. We hope to influence and improve how research in this field is reported by providing a structured list of the defining characteristics. Finally, some examples of the use of the taxonomy are presented to show how it can serve to gather information for characterizing AR-supported collaborative work, and illustrate its potential as the grounds to elicit further studies.

Even with the growth of digital data sources and support for creating visualizations, much information disseminated in chart format is still static, whether printed or digital. Some common problems of visualization components can be easily corrected on the chart design using a charting tool, but in the real world, mainly in the printed media, it is not a simple task. We investigate a method to reconstruct visualizations in real-time and in a real-world environment using Augmented Reality. We propose a prototype that interacts with extracted data from a bitmap chart in the real world, and we evaluated it with usability experts. The results show a high degree of satisfaction on many factors, mainly filter usage and valuable feedback about interaction.

Augmented Reality (AR) has been explored with the objective to assist in scenarios of co-located or remote collaboration. To help understand how well collaborative work can be addressed with AR, it is important to foster harmonization of perspectives and create a common ground for systematization and discussion. In this vein, understand relationships among existing dimensions of collaboration, as well as identify research opportunities, is of paramount importance and thus tools that allow visually exploring information associated with Collaborative AR may be most valuable. In this paper, we present a first effort towards the creation of such an interactive visualization tool for exploration and analysis of collaborative AR research. It allows visualize data of selected papers organized according to a human-centered taxonomy on collaborative AR. In order to get insights into whether the structure was understood and if the representation was clear and efficient to use, we evaluated the proposed tool through a user study with 40 participants. Results suggest the tool has potential towards the creation of a shared understanding and identification of existing patterns, trends and opportunities within the field of collaborative AR.

In many situations, performing maintenance procedures can be facilitated by providing on-site professionals with the possibility to request assistance from remote experts, thus performing the task collaboratively. Since remote experts don't have access to the local environment, they need additional mechanisms to provide instructions and guidance in such context. In this ongoing work, we present a Mixed Reality (MR) platform that explores the use of a shared model approach for collaboration scenarios. The platform uses predefined 3D models, which can be accessed by remote experts using Virtual Reality (VR) and by on-site users through Augmented Reality (AR). In addition, the remote expert can manipulate virtual models using different interaction methods and devices, as a mouse and a keyboard (computer), an interactive projector (touch) and controllers (Head Mounted Display). Our goal was to enrich his experience and improve collaborative awareness. We conducted a preliminary user study to evaluate collaboration, and different interaction methods, using as case study the assembly of Lego blocks.

Artificial Intelligent (AI) techniques, such as ma-chine learning (ML), have been making significant progress over the past decade. Many systems have been applied in sensitive tasks involving critical infrastructures which affect human well-being or health. Before deploying an AI system, it is necessary to validate its behavior and guarantee that it will continue to perform as expected when deployed in a real-world environment. For this reason, it is important to comprehend specific aspects of such systems. For example, understanding how neural networks produce final predictions remains a fundamental challenge. Existing work on interpreting neural network predictions for images via feature visualization often focuses on explaining predictions for neurons of one single convolutional layer. Not presenting a global perspective over the features learned by the model leads the user to miss the bigger picture. In this work we focus on providing a representation based on the structure of deep neural networks. It presents a visualization able to give the user a global perspective over the feature maps of a convolutional neural network (CNN) in a single image, revealing potential problems of the learning representations present in the network feature maps.

The FICA project - Tools for Identifying and Combating Dropout - started at the University of Aveiro in 2015 with the aim to help reduce and prevent dropouts and increase academic success among university students. Within the project a signicant amount of data is provided to different University stakeholders to monitor academic issues, however, these data are currently provided in large tables, a format difficult to analyze. In this paper, we present the main aspects of the data, the users and contexts of use. We also propose an approach to allow the visual and interactive exploration of the FICA project data to help monitor the path of the students and identify risk indicators and failure factors that can lead to critical situations such as dropout. A solution developed using the participatory design methodology is presented, detailing all stages of its creation process, from the requirements elicitation based on focus groups and interviews, design and prototype development in Power BI to its evaluation. Some suggestions for future work are also presented.

This paper presents an approach to support the planning of tourist trips. E-tinerary, provides information on possible points of interest to visit, allowing the expression of preferences and limitations on various aspects. The main objective is to maximize the number of visits in the time available, while reducing the travel time between locations. E-tinerary allows to discover new places to visit, plan sightseeing trips and interact with other users, particularly through viewing and using shared travel plans. Additionally, it is possible to customize travel plans using information about preferred places to visit, available budget, etc. A user-centered design approach was used. Firstly, the profiles of several types of target users, their usage contexts, needs and motivations were characterized, based on which relevant requirements were identified in support of tourism travel planning. Low-fidelity prototypes of an application were created where the developed concepts were demonstrated and evaluated with users. This allowed validate the proposed functionalities and the user interface conceptual model. The application was then developed, providing information needed for travel planning by obtaining external data from APIs such as Google Maps Platform, OpenWeatherMap, and Wikipedia, and aims to propose tours based on route optimization methods, taking into account preferences and limitations expressed by the user. Finally, usability tests were carried out with participants with different profiles; results suggest that E-tinerary was positively evaluated and they would recommend its usage.

Mixed reality (MR) is well suited for situated visualization (SV), a method to represent data in a context, with potential in many situations. However, MR-based visualizations are commonly constrained to the users' single egocentric viewpoint reducing their ability to explore all the available information. This article discusses the main limitations and challenges of this approach based on the analysis of existing literature and identifies opportunities, as well as relevant aspects that must be considered when devising new methods aimed at overcoming those limitations.

Assembly procedures are a common task in several domains of application. Augmented Reality (AR) has been considered as having great potential in assisting users while performing such tasks. However, poor interaction design and lack of studies, often results in complex and hard to use AR systems. This paper considers three different interaction methods for assembly procedures (Touch gestures in a mobile device; Mobile Device movements; 3D Controllers and See-through HMD). It also describes a controlled experiment aimed at comparing acceptance and usability between these methods in an assembly task using Lego blocks. The main conclusions are that participants were faster using the 3D controllers and Video see-through HMD. Participants also preferred the HMD condition, even though some reported light symptoms of nausea, sickness and/or disorientation, probably due to limited resolution of the HMD cameras used in the video see-through setting and some latency issues. In addition, although some research claims that manipulation of virtual objects with movements of the mobile device can be considered as natural, this condition was the least preferred by the participants.

The decision-making process and the development of decision support systems (DSS) have been enhanced by a variety of methods originated from information science, cognitive psychology and artificial intelligence over the past years. Situated visualization (SV) is a method to present data representations in context. Its main characteristic is to display data representations near the data referent. As augmented reality (AR) is becoming more mature, affordable and widespread, using it as a tool for SV becomes feasible in several situations. In addition, it may provide a positive contribution to more effective and efficient decision-making, as the users have contextual, relevant and appropriate information to endorse their choices. As new challenges and opportunities arise, it is important to understand the relevance of intertwining these fields. Based on a literature analysis, this paper addresses and discusses current areas of application, benefits, challenges and opportunities of using SV through AR to visualize data in context and to support a decision-making process and its importance in future DSS.

Gamepads and 3D controllers are the main controllers used in most Virtual Environments. Despite being simple to use, these input devices have a number of limitations as fixed layout and difficulty to remember the mapping between buttons and functions. Mobile devices present interesting characteristics that might be valuable in immersive environments: more flexible interfaces, touchscreen combined with onboard sensors that allow new interaction and easy acceptance since these devices are used daily by most users. The work described in this article proposes a solution that uses mobile devices to interact with Immersive Virtual Environments for selection and navigation tasks. The proposed solution uses the mobile device camera to track the Head-Mounted-Display position and present a virtual representation of the mobile device screen; it was tested using an Immersive Virtual Museum as use case. Based on this prototype, a study was performed to compare controller based and mobile based interaction for navigation and selection showing that using mobile devices is viable in this context and offers interesting interaction opportunities.

Skull analysis is the main tool used in anthropology to identify several characteristics such as ancestry, sex, and variations between populations. Yet, skull analysis methods used by anthropologists still rely heavily on direct manipulation and measurement of the skulls producing significant inter and intra observer errors. Direct manipulation also involves risks of damaging the specimens while handling. In recent years computer methods for skull analysis that rely on 3D models of skulls acquired with a 3D scanner have been proposed. This approach gives the possibility to perform analysis otherwise not possible, simultaneously easing the overall process of skull analysis and reducing variability. This paper describes the development of automatic and semi-automatic methods for morphological analysis of 3D skull models through the extraction and classification of structures aiming to support the estimation of ancestry. Results with fifty specimens are presented

Abstract This paper presents the latest advances and research in Computer Graphics education in a nutshell. It is concerned with topics that were presented at the Education Track of the Eurographics Conference held in Lisbon in 2016. We describe works corresponding to approaches to Computer Graphics education that are unconventional in some way and attempt to tackle unsolved problems and challenges regarding the role of arts in computer graphics education, the role of research‐oriented activities in undergraduate education and the interaction among different areas of Computer Graphics, as well as their application to courses or extra‐curricular activities. We present related works addressing these topics and report experiences, successes and issues in implementing the approaches.

This paper presents a new web-based tool which allows the visualization of real online data combined with other relevant information for supporting tourist trip planning decisions. The main decisions intended supporting concern location, namely place to stay, and routing, which sites to visit and the best sequence to visit them. As they are interconnected, location and routing should be addressed simultaneously. The integrated view has been addressed in the literature from a modeling and solution approach perspective, however, lack of comprehensive visualization solutions to help the decision-making process may hinder their real-world applicability. Although this work focuses on a specific application, the tool presented herein can support other real-world location-routing applications (e.g. in logistics). It enables interactive visualizations and navigation in web browsers, and provides functionalities considered important in the context of tourist trip planning. Focus group and usability evaluation were used throughout the development of the tool for collecting information and testing visualizations and interactions.

Multi-objective optimization models have been increasingly used as optimal decisions are searched in settings considering several conflicting objectives. In these cases compromises must be made and often a large number of non-dominated optimal solutions exist. From these solutions decision-makers must find the preferred one. This is a difficult task both from a computational and cognitive point of views, as it requires several solutions to be obtained and compared. An interactive visualization tool for fully understanding the best trade-offs is therefore becoming increasingly important. This paper proposes visualization solutions, implemented in a tool, for aiding decision-makers in finding the preferred solution in multi-objective optimization problems.

Left ventricle functional analysis can be performed using coronary CT angiography (CTA) images. In recent years it has been proposed that CTA imaging might also be used for myocardial perfusion assessment, by visually looking for hypoattenuated regions that may correspond to hypoperfusion. Assigning a detected lesion to a specific myocardial segment requires significant effort while the clinician matches the American Heart Association (AHA) standard myocardial segments to the anatomy of each patient. This article presents an interactive tool which, based on the existence of a previous left ventricle segmentation, automatically matches the lesions detected by the clinician to a myocardial segment and provides feedback over the image regarding the myocardial segments with detected lesions and their severity.

This work presents an ongoing work on a new approach to perform craniometric analysis based on contactless 3D modelling of skulls. Beside the acquisition process with a 3D range sensor and initial results in the semi-automatic detection of features in the skulls, we also present some results in the development of a 3D interactive interface that eases interaction for users with little experience on digital 3D manipulation. The final objective is to provide an easy to use 3D interface to allow semi-automatic detection of features in skulls. It is our belief that this system might be the first step towards a new methodology for craniometric analysis that can solve several of the current problems such as repeatability, wide access to skull information or bone damage during measurements.

Visualizing large family structures is becoming increasingly important, as more genealogical data becomes available. A space-filling h-tree layout pedigree has been recently proposed to make better use of the available space than traditional representations. In a previous paper we applauded the technique's usage of available space but remarked that it makes generation identification difficult and does not allow navigating to descendants of represented individuals. A set of extensions was proposed to help overcome these limitations and a preliminary evaluation suggested that those extensions enhance the original technique. This paper presents a more thorough evaluation carried out to assess if and how the proposed extensions improve the original h-tree layout pedigree technique. Results suggest that these extensions improve user performance on some tasks, effectively provide new functionality, and generally enhance user experience.

Geophysical data represent subsoil structure in a specific area and can be used to extract subsoil information for various purposes. In this work we used this data type to detect anomalies/contamination in the subsoil. Our case study was based on data acquired around a landfill and the main objective is identifying contaminated areas as a result of leakage in landfill. This involves the application of statistical methods to detect anomalous values taking into account the whole data set, subdividing it in sublevels in relation to the surface, instead of using a single threshold (as usual). This work combines in the same software package the anomaly statistical analysis and several 3D representations of the results to validate and also helps understanding the final results of the analysis. Given that the original data used in the analysis, resistivity sections, is normally very sparse, a kriging geostatistical process was used to interpolate data in order to provide a volumetric representation of the subsoil in the area, providing a continuous spatial visualization.

The constant growth of available genealogical information has encouraged the research of visualization techniques capable of representing the corresponding large amount of data. An H-Tree Layout has been recently proposed to represent pedigree data as a way to overcome some of the limitations of traditional representations. However, this new method has its own limitations which may hinder its adoption. In this paper, we propose some enhancements to the H-Tree Layout pedigree visualization method in order to overcome some of the identified limitations. An implementation of the proposed enhancements and results of a preliminary evaluation are also provided.

Abstract Coronary CT angiography is widely used in clinical practice for the assessment of coronary artery disease. Several studies have shown that the same exam can also be used to assess left ventricle (LV) function. Even though coronary CT angiography provides data concerning multiple cardiac phases, along the cardiac cycle, LV function is usually evaluated using just the end‐systolic and end‐diastolic phases. This unused wealth of data, mostly due to its complexity and the lack of proper tools, has still to be explored to assess if further insight is possible regarding regional LV functional analysis. Furthermore, different parameters can be computed to characterize LV function and though some are well known by clinicians others still need to be tested concerning their value in clinical scenarios. Based on these premises, we present several parameters characterizing global and regional LV function, computed for several cardiac phases over one cardiac cycle. The data provided by the computed parameters is shown using a set of visualizations allowing synchronized visual exploration of the different data. The main purpose is to provide means for clinicians to explore the data and gather insight over their meaning and their correlation with each other and with diagnosis outcomes.

The work presented in this paper aims at exploring new ways of integrating, visualizing and interacting with geotechnical and geophysical data that may be more rich and interactive than those offered by most current Geographic Information Systems (GIS). Some visualization techniques enabling simultaneous visualization of the several data types available in our case study are proposed. Moreover, methods were developed to guide experts while defining layers and other relevant geological structures. The work is still in an early stage and is main goal has been assessing the validity and adequacy of the proposed techniques to the specific geotechnical and geophysical data under consideration.

Facility location and vehicle routing are amongst the most important logistic decisions in today's organizations. These aspects are intertwined and, in some cases, should be addressed in an integrated way (giving rise to the location-routing approach). A decision support tool that can make easier the visualization (and editing) of information regarding these problems is becoming increasingly important as: it enables to further understand the problem at hand; and, at the same time, it fosters better communication of the decisions in a way easier to understand by the general public. This paper presents some concepts for information visualization on the problems arisen by the aforementioned decisions, which have been incorporated in a decision support tool and tested using usability evaluation methods.

This paper presents a user study performed to compare the usability of the Wiimote as an input device to visualize information and navigate in Google Earth using two different configurations. This study had the collaboration of 15 participants which performed a set of tasks using the Wiimote as an input device while the image was projected on a common projection screen, as well as a mouse on a desktop. Results show that most users clearly preferred one of the Wiimote configurations over the other, and over the mouse; moreover, they had better performances using the preferred configuration, and found it easier to use.

Cardiac angiography using multiple detector row computerized tomography (MDCT) scanners provides 3D data concerning the heart and, in particular, the left ventricle (LV), for different cardiac phases along one cardiac cycle. Exploring this data for LV function analysis is not an easy task, given the amount of data and time involved in segmenting (or revising results provided by automatic segmentation methods) up to 12 cardiac phases. CardioAnalyser, a tool for 4D LV segmentation from MDCT data which provides a protocol to help perform LV segmentation of all cardiac phases available is presented. It uses an automatic segmentation algorithm along with a procedure which guides the user through the process. Its main goal is to reuse as much information as possible from one cardiac phase to the next in order to reduce segmentation time and the amount of user interaction.

The appropriate use of color in Visualization is a very important subject. The choice of the proper color scale to use with a particular data set is not just a matter of choosing the prettiest representation. Throughout the years researchers have studied this subject and managed to propose guidelines which help users along the process of color scale selection. This article presents a brief overview on the subject focusing on the desired properties for color scales, the guidelines that should drive their choice, the advantages of applying those guidelines, the experimental research work on the field, and the tools proposed to help non-expert users.

Polygonal meshes are used in many areas to model different objects and structures. Depending on their applications, they sometimes have to be processed to, for instance, reduce their complexity (simplification). This mesh processing introduces error, whose evaluation is important when choosing the kind of processing that is to be done for a particular application. Although some mesh comparison tools are described in the literature, little attention has been given to the way results are presented. A tool is presented which enhances the way users perform mesh analysis and comparison, by providing an environment where several visualization options are available and can be used in a coordinated way.

This work presents a set of visualization methods incorporated in a system for internal technologically mediated communication and information management. This system, which assumes an organizational context and an intranet built on World Wide Web technologies and services, was developed in order to allow a manager to evaluate the efficiency, effectiveness and adequacy of the intranet to the organization's mission. The visualization methods and the raw information that is gathered are explained. Some examples are shown and discussed alongside some preliminary research results. The system user interface, including visually correlated visualization strategies, is also briefly presented.

This work presents a general description of the methods used in the on-going evaluation of a Visualizer, which is a sub-component of the Web Log Visual Analysis System. We are trying to evaluate some aspects of the user interface and visualization techniques implemented as part of the prototype. Observation and querying techniques were used with two types of users. A general description of those users and methods is presented. Preliminary results were encouraging and provided new ideas and information that will, eventually, allow a more complete and formal evaluation of our application.

The problem of locating obnoxious facilities has become a major social concern. Operations research models and methods have been used in this context, however their use can be jeopardised by the huge demanded effort. In consequence, the use of visualization and interaction methods becomes of great importance. This paper addresses specific issues and shows examples of developed solutions for the visualization and interaction problems related to the use of mono and multicriteria obnoxious facility location in decision support scenarios.

A set of parameters to assess the objective quality of visualizations of a voxel-based data set, produced using a ray caster, is proposed as a first step toward the evaluation of the overall quality of these visualizations. Results obtained using synthetic data and a simple implementation of a ray caster are presented. The final goal of this evaluation is the computation of "confidence indices" that could offer the user a "guided visualization", i.e. allow him/her to decide what are the "best" visualizations of a data set.