Spatial perception in virtual environments has been a topic of intense research. Arguably, the majority of this work has focused on distance perception. However, orientation perception is also an important factor. In this paper, we systematically investigate allocentric orientation judgments in both real and virtual contexts over the course of four experiments. A pattern of sinusoidal judgment errors known to exist in 2D perspective displays is found to persist in immersive virtual environments. This pattern also manifests itself in a real world setting using two differing judgment methods. The findings suggest the presence of a radial anisotropy that persists across viewing contexts. Additionally, there is some evidence to suggest that observers have multiple strategies for processing orientations but further investigation is needed to fully describe this phenomenon. We also offer design suggestions for 3D user interfaces where users may perform orientation judgments.

Following their introduction in the 1960s, head-mounted VR systems mainly focused on visual and aural senses. In order to enhance immersion in the virtual world, researchers have since pursued the addition of movement and haptics through motion platforms, exoskeletons, and other hand-held devices. From a proliferation of low-cost devices that can sense the user's motion to full body motion capture suits, from gloves to gestures, natural interaction techniques have been desirable and explored in HCI and VR for several years. With virtual reality rapidly becoming accessible to mass audiences, there is growing interest in new forms of natural input techniques to enhance immersion and engagement in multiuser systems. First we need to determine what types of techniques can we design that would integrate well with multiuser experiences. Next, we need to understand the contribution of the designed techniques to the experience, understand how they work with existing controllers, and explore whether they should replace or augment current techniques in order to design more effective and engaging experiences. Finally, it is vital to discern the limitations and the types of application scenarios that are suitable for incorporating the techniques. The aim of this workshop is to deepen and expand the discussion on natural interaction techniques for collaborative VR within the CHI community and promote their relevance and research in HCI.

Projected displays can present life-sized imagery of a virtual human character that can be seen by multiple observers. However, typical projected displays can only render that virtual human from a single viewpoint, regardless of whether head tracking is employed. This results in the virtual human being rendered from an incorrect perspective for most individuals in a group of observers. This could result in perceptual miscues, such as the “Mona Lisa” effect, causing the virtual human to appear as if it is simultaneously gazing and pointing at all observers in the room regardless of their location. This may be detrimental to training scenarios in which all trainees must accurately assess where the virtual human is looking or pointing a weapon. In this paper, we discuss our investigations into the presentation of eye gaze using REFLCT, a previously introduced head mounted projective display. REFLCT uses head tracked, head mounted projectors and retroreflective screens to present personalized, perspective correct imagery to multiple users without the occlusion of a traditional head mounted display. We examined how head mounted projection for enhanced presentation of eye gaze might facilitate or otherwise affect social interactions during a multi-person guessing game of “Twenty Questions.”

Virtual objects are essential for building environments in virtual reality (VR) applications. However, creating photorealistic 3D models is not easy, and handcrafting the detailed 3D model from a real object can be time and labor intensive. An alternative way is to build a structured camera array such as a light-stage to reconstruct the model from a real object. However, these technologies are very expensive and not practical for most users. In this work, we demonstrate a complete end-to-end pipeline for the capture, processing, and rendering of view-dependent 3D models in virtual reality from a single consumer-grade RGB-D camera. The geometry model and the camera trajectories are automatically reconstructed from a RGB-D image sequence captured offline. Based on the HMD position, selected images are used for real-time model rendering. The result of this pipeline is a 3D mesh with view-dependent textures suitable for real-time rendering in virtual reality. Specular reflections and light-burst effects are especially noticeable when users view the objects from different perspectives in a head-tracked environment.

Visualization is a critical component of neuroimaging, and how to best view data that is naturally three dimensional is a long standing question in neuroscience. Many approaches, programs, and techniques have been developed specifically for neuroimaging. However, exploration of 3D information through a 2D screen is inherently limited. Many neuroscientific researchers hope that with the recent commercialization and popularization of VR, it can offer the next-step in data visualization and exploration. Neuro Imaging in Virtual Reality (NIVR), is a visualization suite that employs various immersive visualizations to represent neuroimaging information in VR. Some established techniques, such as raymarching volume visualization, are paired with newer techniques, such as near-field rendering, to provide a broad basis of how we can leverage VR to improve visualization and navigation of neuroimaging data. Several of the neuroscientific visualization approaches presented are, to our knowledge, the first of their kind. NIVR offers not only an exploration of neuroscientific data visualization, but also a tool to expose and educate the public regarding recent advancements in the field of neuroimaging. By providing an engaging experience to explore new techniques and discoveries in neuroimaging, we hope to spark scientific interest through a broad audience. Furthermore, neuroimaging offers deep and expansive datasets; a single scan can involve several gigabytes of information. Visualization and exploration of this type of information can be challenging, and real-time exploration of this information in VR even more so. NIVR explores pathways which make this possible, and offers preliminary stereo visualizations of these types of massive data.

High-fidelity virtual content is essential for the creation of compelling and effective virtual reality (VR) experiences. However, creating photorealistic content is not easy, and handcrafting detailed 3D models can be time and labor intensive. Structured camera arrays, such as light-stages, can scan and reconstruct high-fidelity virtual models, but the expense makes this technology impractical for most users. In this paper, we present a complete end-to-end pipeline for the capture, processing, and rendering of view-dependent 3D models in virtual reality from a single consumer-grade depth camera. The geometry model and the camera trajectories are automatically reconstructed and optimized from a RGB-D image sequence captured offline. Based on the head-mounted display (HMD) position, the three closest images are selected for real-time rendering and fused together to smooth the transition between viewpoints. The specular reflections and light-burst effects can also be preserved and reproduced. We confirmed that our method does not require technical background knowledge by testing our system with data captured by non-expert operators.

We believe that virtual humans, presented over video chat services, such as Skype, and delivered using smartphones, can be an effective way to deliver innovative applications where social interactions are important, such as counseling and coaching. To explore this subject, we have built a hardware and software apparatus that allows virtual humans to initiate, receive, and interact over video calls using Skype or any similar service. With this platform, we conducted two experiments to investigate the applications and characteristics of virtual humans that interact over mobile video. In Experiment 1, we investigated user reactions to the physical realism of the background scene in which a virtual human was displayed. In Experiment 2, we examined how virtual characters can establish and maintain longer term relationships with users, using ideas from Social Exchange Theory to strengthen bonds between interactants. Experiment 2 involved repeated interactions with a virtual human over a period of time. Both studies used counseling-style interactions with users. The results demonstrated that males were more attracted socially to a virtual human that was presented over a realistic background than a featureless background while females were more socially attracted to a virtual human with a less realistic featureless background. The results further revealed that users felt the virtual human was a compassionate partner when they interacted with the virtual human over multiple calls, rather than just a single call.

With the imminent emergence of low-cost tracking solutions, everyday VR users will soon experience the enhanced immersion of natural walking. Even with consumer-grade room-scale tracking, exploring large virtual environments can be made possible using a software solution known as redirected walking. Wide adoption of this technique has been hindered by the complexity and subtleties involved in successfully deploying redirection. To address this matter, we introduce the Redirected Walking Toolkit, to serve as a unified platform for developing, benchmarking, and deploying redirected walking algorithms. Our design enables seamless integration with standard virtual reality configurations, requiring minimal setup effort for content developers. The toolkit's flexible architecture offers an interface that is not only easy to extend, but also complimented with a suite of simulation tools for testing and analysis. We envision the Redirected Walking Toolkit to be a common testbed for VR researchers as well as a publicly-available tool for large virtual exploration in virtual reality applications.

We present a system for creating and displaying interactive life-sized 3D digital humans based on pre-recorded interviews. We use 30 cameras and an extensive list of questions to record a large set of video responses. Users access videos through a natural conversation interface that mimics face-to-face interaction. Recordings of answers, listening and idle behaviors are linked together to create a persistent visual image of the person throughout the interaction. The interview subjects are rendered using flowed light fields and shown life-size on a special rear-projection screen with an array of 216 video projectors. The display allows multiple users to see different 3D perspectives of the subject in proper relation to their viewpoints, without the need for stereo glasses. The display is effective for interactive conversations since it provides 3D cues such as eye gaze and spatial hand gestures.

Redirected walking techniques have been introduced to overcome physical space limitations for natural locomotion in virtual reality. These techniques decouple real and virtual user trajectories by subtly steering the user away from the boundaries of the physical space while maintaining the illusion that the user follows the intended virtual path. Effectiveness of redirection algorithms can significantly improve when a reliable prediction of the users future virtual path is available. In current solutions, the future user trajectory is predicted based on non-standardized manual annotations of the environment structure, which is both tedious and inflexible. We propose a method for automatically generating environment annotation graphs and predicting the user trajectory using navigation meshes. We discuss the integration of this method with existing redirected walking algorithms such as FORCE and MPCRed. Automated annotation of the virtual environments structure enables simplified deployment of these algorithms in any virtual environment.

With the recent proliferation of high-fidelity head-mounted displays (HMDs), there is increasing demand for realistic 3D content that can be integrated into virtual reality environments. However, creating photorealistic models is not only difficult but also time consuming. A simpler alternative involves scanning objects in the real world and rendering their digitized counterpart in the virtual world. Capturing objects can be achieved by performing a 3D scan using widely available consumer-grade RGB-D cameras. This process involves reconstructing the geometric model from depth images generated using a structured light or time-of-flight sensor. The colormap is determined by fusing data from multiple color images captured during the scan. Existing methods compute the color of each vertex by averaging the colors from all these images. Blending colors in this manner creates low-fidelity models that appear blurry. (Figure 1 right). Furthermore, this approach also yields textures with fixed lighting that is baked on the model. This limitation becomes more apparent when viewed in head-tracked virtual reality, as the illumination (e.g. specular reflections) does not change appropriately based on the user's viewpoint.

In this article, we detail a series of experiments that examines the effect of vertical field-of-view extension and the addition of non-specific peripheral visual stimulation on gait characteristics and distance judgments in a head-worn virtual environment. Specifically, we examined four field-of-view configurations: a common 60° diagonal field of view (48° × 40°), a 60° diagonal field of view with the addition of a luminous white frame in the far periphery, a field of view with an extended upper edge, and a field of view with an extended lower edge. We found that extension of the field of view, either with spatially congruent or spatially non-informative visuals, resulted in improved distance judgments and changes in observed posture. However, these effects were not equal across all field-of-view configurations, suggesting that some configurations may be more appropriate than others when balancing performance, cost, and ergonomics.

Redirected walking enables the exploration of large virtual environments while requiring only a finite amount of physical space. Unfortunately, in living room sized tracked areas the effectiveness of common redirection algorithms such as Steer-to-Center is very limited. A potential solution is to increase redirection effectiveness by applying two types of perceptual manipulations (curvature and translation gains) simultaneously. This paper investigates how such combination may affect detection thresholds for curvature gain. To this end we analyze the estimation methodology and discuss selection process for a suitable estimation method. We then compare curvature detection thresholds obtained under different levels of translation gain using two different estimation methods: method of constant stimuli and Green's maximum likelihood procedure. The data from both experiments shows no evidence that curvature gain detection thresholds were affected by the presence of translation gain (with test levels spanning previously estimated interval of undetectable translation gain levels). This suggests that in practice currently used levels of translation and curvature gains can be safely applied simultaneously. Furthermore, we present some evidence that curvature detection thresholds may be lower that previously reported. Our estimates indicate that users can be redirected on a circular arc with radius of either 11.6m or 6.4m depending on the estimation method vs. the previously reported value of 22m. These results highlight that the detection threshold estimates vary significantly with the estimation method and suggest the need for further studies to define efficient and reliable estimation methodology.

ShodanVR is an immersive visualization for querying and displaying text records from the Shodan database of Internet connected devices. Shodan provides port connection data retrieved from servers, routers, and other networked devices [2]. Cybersecurity professionals can glean this data for device populations, software versions, and potential security vulnerabilities [1].

Redirection techniques allow users to explore large virtual environments on foot while remaining within a limited physical space. However, research has primarily focused on redirection through manipulation of the visuals used to represent the virtual environment. We describe a within-subjects study (n=31) exploring if participants' ability to detect differences between real and virtual rotations is influenced by the addition of sound that is spatially aligned with its virtual source. The results revealed similar detection thresholds for conditions involving moving audio, static audio, and no audio. This may be viewed as an indication of visual dominance during scenarios such as the one used for the current study.

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A facial image capture system may capture images of a face of a person while the person is moving. A video camera may capture sequential images of a scene to which the video camera is directed. A marker-based location detection system may determine and generate information about the location of a marker worn on or close to the face of the person. A camera control system may automatically adjusts both the horizontal and vertical direction to which the video camera is directed so as to cause the sequential images of the camera to each be of the face of the person while the person is moving, based on the information about the location of the marker from the marker-based location detection system.

There is rapidly growing interest in the creation of rendered environments and content for tracked head-mounted stereoscopic displays for virtual reality. Currently, the most popular approaches include polygonal environments created with game engines, as well as 360 degree spherical cameras used to capture live action video. These tools were not originally designed to leverage the more complex visual cues available in VR when users laterally shift viewpoints, manually interact with models, and employ stereoscopic vision. There is a need for a fresh look at graphics techniques that can capitalize upon the unique affordances that make VR so compelling.