Virtual Reality applications increasingly require methods to effectively guide users to important elements within the virtual environment. Central visual cues are the most common method, which have proven effective for directing attention, yet often compromise on level of immersion. This work explored whether peripheral visual cues could serve as an alternative approach that supports attention guidance while preserving sense of presence. We performed a user study with 24 participants to compare four visual cues: two central cues (Floating Text and Floating Arrow) and two peripheral cues (Edge Lighting and Swarm). Users completed a visual search task of 7 objects for each visual cue, with data collected on performance through reaction time, round time, and total errors. Additionally, presence and workload were evaluated through the IGROUP Presence Questionnaire and NASA Task Load Index, respectively. No statistically significant differences were found between peripheral and central cues for presence, however performance and workload varied significantly based on specific cue implementation rather than type of positioning. Our findings indicate that peripheral positioning does not inherently provide attention guidance advantages over central placement. Instead, thoughtful cue design, with a simple yet clear appearance and behavior appears to be the critical factor for achieving effective attention guidance while preserving presence in IVEs. These results provide valuable insights for VR content creators to facilitate the design process of VR experiences.

Abstract Collaboration in extended reality (XR) environments presents complex challenges that revolve around how users perceive the presence, intentions, and actions of their collaborators. This paper delves into the intricate realm of group awareness, focusing specifically on workspace awareness and the innovative visual cues designed to enhance user comprehension. The research begins by identifying a spectrum of collaborative situations drawn from an analysis of XR prototypes in the existing literature. Then, we describe and introduce a novel classification for workspace awareness, along with an exploration of visual cues recently employed in research endeavors. Lastly, we present the key findings and shine a spotlight on promising yet unexplored topics. This work not only serves as a reference for experienced researchers seeking to inform the design of their own collaborative XR applications but also extends a welcoming hand to newcomers in this dynamic field.

DeskVR allows users to experience Virtual Reality (VR) while sitting at a desk without requiring extensive movements. This makes it better suited for professional work environments where productivity over extended periods is essential. However, tasks that typically resort to mid-air gestures might not be suitable for DeskVR. In this paper, we focus on the fundamental task of object selection. We present TouchRay, an object selection technique conceived specifically for DeskVR that enables users to select objects at any distance while resting their hands on the desk. It also allows selecting objects’ sub-components by traversing their corresponding hierarchical trees. We conducted a user evaluation comparing TouchRay against state-of-the-art techniques targeted at traditional VR. Results revealed that participants could successfully select objects in different settings, with consistent times and on par with the baseline techniques in complex tasks, without requiring mid-air gestures.

Virtual reality (VR) has the potential to significantly boost productivity in professional settings, especially those that can benefit from immersive environments that allow a better and more thorough way of visualizing information. However, the physical demands of mid-air movements make it difficult to use VR for extended periods. DeskVR offers a solution that allows users to engage in VR while seated at a desk, minimizing physical exhaustion. However, developing appropriate motion techniques for this context is challenging due to limited mobility and space constraints. This work focuses on object manipulation techniques, exploring touch-based and mid-air-based approaches to design a suitable solution for DeskVR, hypothesizing that touch-based object manipulation techniques could be as effective as mid-air object manipulation in a DeskVR scenario while less physically demanding. Thus, we propose Scaled Indirect Touch 6-DOF (SIT6), an indirect touch-based object manipulation technique incorporating scaled input mapping to address precision and out-of-reach manipulation issues. The implementation of our solution consists of a state machine with error-handling mechanisms and visual indicators to enhance interaction. User experiments were conducted to compare the SIT6 technique with a baseline mid-air approach, revealing comparable effectiveness while demanding less physical exertion. These results validated our hypothesis and established SIT6 as a viable option for object manipulation in DeskVR scenarios.

Haptic feedback in Virtual Reality is commonly provided through wearable or grounded devices adapted to specific scenarios and situations. Shape-changing devices allow for the physical representation of different virtual objects but are still a minority, complex, and usually have long transformation times. We present Shape-a-getti, a novel ungrounded, non-wearable, and graspable haptic device that can quickly change between different radially symmetrical shapes. It uses a single actuator to rotate several identical poles distributed along a radius to render the different shapes. The format of the poles defines the possible shapes, and in our prototype, we used one that could render concave, straight, and convex shapes with different radii. We conducted a user evaluation with 21 participants asking them to recognize virtual objects by grasping the Shape-a-getti. Despite having difficulties distinguishing between some objects with very similar shapes, participants could successfully identify virtual objects with different shapes rendered by our device.

Typical VR interactions can be tiring, including standing up, walking, and mid-air gestures. Such interactions result in decreased comfort and session duration compared with traditional non-VR interfaces, which may, in turn, reduce productivity. Nevertheless, current approaches often neglect this aspect, making the VR experience not as promising as it can be. As we see it, desk VR experiences provide the convenience and comfort of a desktop experience and the benefits of VR immersion, being a good compromise between the overall experience and ergonomics. In this work, we explore navigation techniques targeted at desk VR users, using both controllers and a large multi-touch surface. We address travel and orientation techniques independently, considering only continuous approaches for travel as these are better suited for exploration and both continuous and discrete approaches for orientation. Results revealed advantages for a continuous controller-based travel method and a trend for a dragging-based orientation technique. Also, we identified possible trends towards task focus affecting overall cybersickness symptomatology.

Information visualization commonly aids the understanding of the evolution of spatiotemporal phenomena. The current work proposes a novel approach to visually represent spatiotemporal phenomena based on the automated generation of static and interactive visual narratives that summarize the evolution of a spatiotemporal phenomenon. The visual narrative is composed of an interactive storyboard that consists of a set of frames that represent events of interest in the phenomenon. Towards corroborating the hypothesis that this approach would effectively and efficiently transmit the evolution of spatiotemporal phenomena, we conceptualized a visualization framework, identifying visual metaphors that map spatiotemporal transformations into visual content and defining the parameterization approaches for spatiotemporal features. We developed a functional prototype implementing the conceptual solution and presented issues encountered regarding visual clutter and parameterization. We conducted a user study based on a questionnaire which concluded that the proposed approach can be effective and efficient for understanding the evolution of these phenomena in terms of transformations for a subset of possible scenarios.

Healthcare centers are ideal settings to identify and motivate parents to adhere to healthier lifestyles in order to reverse their child's excessive weight. However, such promotions are time- and resource-consuming, and primary health care needs new approaches to engage parents. In this article, we present an app for that purpose, with tailored recommendations for parents regarding young children's lifestyles (eating, drinking, moving, and sleeping habits) with gamification mechanics for parents, and a serious game for their children, aged 3-6 years. Healthcare center based questionnaires were used to assess parent's acceptance of the app. We also determined their enrollment and retention rates with a pilot study, in order to test the implementation of a randomized controlled trial (RCT) in the future (pilot trial registration: ClinicalTrials.gov NCT03881280). In the pilot study, we tested their engagement with the app during a four-week period through a monitoring website. In the acceptance test (n = 13), parents rated the app a median score of seven on a ten-point scale. In the pilot study (n = 21), all parents in the intervention group used the app. The retention rate was 71.4%. This study indicated some areas of improvement related to gaming mechanics in order to increase participation. Healthcare center's professionals and parents of children with overweight/obesity accepted this innovative approach. In addition, it is feasible to test its impact on children's lifestyle by conducting an RCT in the future.

This paper proposes a haptic interaction system for Virtual Reality (VR) based on a combination of tracking devices for hands and objects and a real-to-virtual mapping system for user redirection. In our solution the user receives haptic stimuli by manipulating real objects mapped to virtual ob- jects. This solution departs from systems that rely on haptic devices (e.g., haptic gloves) as interfaces for the user to inter- act with objects in the Virtual Environment (VE). As such, the proposed solution makes use of direct haptics (touching) and redirection techniques to guide the user through the vir- tual environment. Using the mapping framework, when the user touches a virtual object in the VE, he will simultane- ously be physically touching the equivalent real object. A relevant feature of the framework is the possibility to de- fine a warped mapping between the real and virtual worlds, such that the relation between the user and the virtual space can be different from the one between the user and the real space. This is particularly useful when the application re- quires the emulation of large virtual spaces but the physical space available is more confined. To achieve this, both the user's hands and the objects are tracked. In the presented prototype we use a head-mounted depth sensor (i.e., Leap Motion) and a depth-sensing camera (i.e., Kinect). To assess the feasibility of this solution, a functional prototype and a room setup with core functionality were implemented. The test sessions with users evaluated the mapping accuracy, the user execution time and the awareness of the user regarding the warped space when performing tasks with redirection. The results gathered indicate that the solution can be used to provide direct haptic feedback in VR applications and for warping space perception within certain limits.

With the rising research in emotionally believable agents, several advances in agent technology have been made, ranging from interactive virtual agents to emotional mechanism simulations and emotional agent architectures. However, creating an emotionally believable agent capable of emotional though t is still largely out of reach. It has been proposed that being able to accurately model human emotion would allow agents to mimic human behaviour while these models are studied to create more accurate theoretical models. In light of these challenges, we present a general method for human emotional state modelling in interactive environments. The proposed method employs a three-layered classification process to model the arousal and valence (i.e., hedonic) emotional components, based on four selected psychophysiological metrics. Additionally, we also developed a simplified version of our system for use in real-time systems and low-fidelity applications. The modelled emotional states by both approaches compared favourably with a manual approach following the current best practices reported in the literature while also improving on its predictive ability. The obtained results indicate we are able to accurately predict human emotional states, both in offline and online scenarios with varying levels of granularity; thus, providing a transversal method for modelling and reproducing human emotional profiles.

The development of Advanced Driver Assistance Systems (ADAS) is rapidly growing. However, most of the ADAS require field test, which is expensive, unpredictable and time consuming. In this paper we propose a multiagent-based driving simulator which integrates a human factor analysis suite and enables rapid and low-cost experimentation of mobile-device ADAS. Our architecture uses a microscopic simulator and a serious-game-based driving simulator. The latter allows the user to control a vehicle and change the correspondent simulation state in the microscopic simulator. The driving simulator also connects to an Android device and sends several kinds of data, such as current GPS coordinates or transportation network data. One important feature of this architecture is its suitability to serve as an appropriate means to conduct behaviour elicitation through peer-designed agents, so as to improve modelling of various driving styles accounting for different aspects of preferences and perception abilities, as well as other performance measures related to drivers' interaction with ADAS solutions. The potentials of our approach to aid experiments in human factor analysis are still to be tested, but are undoubtedly huge and encouraging.

This paper presents a robust approach for 3D point reconstruction based on a set of images taken from a static scene with known, but not necessarily exact or regular, camera parameters. The points to be reconstructed are chosen from the contours of images, and a world-based formulation of the reconstruction problem and associated epipolar geometry is used. The result is a powerful mean of transparently integrating contributions from multiple images, and increased robustness to situations such as occlusions or apparent contours. Two steps for adding robustness are proposed: cross-checking, which validates a reconstructed point taken from an image by projecting it on a special subset of the remaining images; and merging, which fuses pairs of reconstructed points that are close in 3D space and that were initially chosen from different images. Results obtained with a synthetic scene (for ground truth comparison and error assessment), and two real scenes show the improved robustness achieved with the steps proposed.