This paper compares the wayfinding differences between Virtual Reality Omnidirectional Treadmills (VR-ODT) locomotion techniques. We aim to identify their effect on users’ spatial exploration while navigating VEs. Our results demonstrate that VR-ODT locomotion techniques resulted in frequent stops and reorientation efforts, particularly at critical decision points within the maze. However, we did not identify differences between the techniques analyzed.

In this work, we present the design and comparative evaluation of techniques for increasing awareness of out-of-view targets in virtual reality. We first compare two variants of SOUS-a technique that guides the user to out-of-view targets using circle cues in their peripheral vision-with the existing FlyingARrow technique, in which arrows fly from the user's central (foveal) vision toward the target. fSOUS, a variant with low visual salience, performed well in a simple environment but not in visually complex environments, while bSOUS, a visually salient variant, yielded faster target selection than both fSous and FlyingARrow across all environments. We then compare hybrid techniques in which aspects of SOUS relating to unobtrusiveness and visual persistence were reflected in design modifications made to FlyingARrow. Increasing persistence by adding trails to arrows improved performance but there were concerns about obtrusiveness, while other modifications yielded slower and less accurate target acquisition. Nevertheless, since fSOUS and bSOUS are exclusively for head-mounted display with wide field-of-view, FlyingARrow with trail can still be beneficial for devices with limited field-of-view.

Headworn Augmented Reality (AR) and Virtual Reality (VR) displays are an exciting new medium for locative storytelling. Authors face challenges planning and testing the placement of story elements when the story is experienced in multiple locations or the environment is large or complex. We present Story CreatAR, the first locative AR/VR authoring tool that integrates spatial analysis techniques. Story CreatAR is designed to help authors think about, experiment with, and reflect upon spatial relationships between story elements, and between their story and the environment. We motivate and validate our design through developing different locative AR/VR stories with several authors.

Very large floor displays can promote engaging public experiences, but incur perspective-related warping, making it challenging to comprehend and interact with distal objects when standing on the display. We introduce a perspective compensated view technique that maintains the relative size and shape of objects as they move away from the viewer, and explore the technique in SpaceHopper, a large-scale, floor-projected version of the game Asteroids. Players bounce on a hopper ball to control their ship in one of two control modes: bounce to repel or bounce to shoot. We evaluated SpaceHopper in a field experiment with 59 participants, finding that perspective compensated view yielded longer playing times (and higher scores) in the bounce to fire modality. Bystanders were highly engaged with players and also seemed to be unaware of the perspective warping, suggesting that visually compensating for the interactor’s perspective does not adversely impact the enjoyment of passive participants and audience members, at least under some circumstances.

Museums are constantly searching for new ways to increase engagement with their exhibits, from electronic guides to modern digital technologies such as special-purpose tablets, smartphones, and virtual and augmented reality (AR). For AR exhibits in particular, promoting shared experience and group cohesion is not straightforward. In this work, we investigate scenarios in which not everyone is using a head-worn display (HWD), either because there aren't enough available or simply because someone might feel uncomfortable using it. We propose two sharing techniques for AR experiences and evaluate them in a long term in-the-wild study: Over-the-Shoulder AR, which renders a real-time virtual representation of the augmented reality content on a large secondary display; Semantic Linking, which displays contextual information about the virtual content on the same large display. We also introduce a complementary technique: Indicator Rings, which display the locations of the HWD user's objects-of-focus. We observed that participants in the Over-the-Shoulder AR and Semantic Linking conditions stayed together and exhibited more verbal exchanges than participants in a Baseline condition, which could indicate that they were more engaged. Self-reported measures indicated an increase in pair communication and increased comprehension of the virtual content for participants without the HWD. Participants without the HWD also displayed a greater understanding of the location of virtual elements with support from the Indicator Rings, and used them as a tool to guide the HWD user through the virtual content. We discuss design implications for interactive augmented reality exhibits and possible applications outside the cultural heritage scenario.

Although users accomplish ever more tasks on touch-enabled mobile devices, gesture-based interaction remains limited and almost never customizable by users. Our goal is to help users create gestures that are both personally memorable and reliably recognized by a touch-enabled mobile device. We address these competing requirements with two dynamic guides that use progressive feedforward to interactively visualize the "negative space" of unused gestures: the Pathward technique suggests four possible completions to the current gesture, and the Fieldward technique uses color gradients to reveal optimal directions for creating recognizable gestures. We ran a two-part experiment in which 27 participants each created 42 personal gesture shortcuts on a smartphone, using Pathward, Fieldward or No Feedforward. The Fieldward technique best supported the most common user strategy, i.e. to create a memorable gesture first and then adapt it to be recognized by the system. Users preferred the Fieldward technique to Pathward or No Feedforward, and remembered gestures more easily when using the technique. Dynamic guides can help developers design novel gesture vocabularies and support users as they design custom gestures for mobile applications.

In this paper, we explore how people use touchscreens to express emotional intensity, and whether these intensities can be understood by oneself at a later date or by others. In a controlled study, 26 participants were asked to express a set of emotions mapped to predefined gestures, at range of different intensities. One week later, participants were asked to identify the emotional intensity visualized in animations of the gestures made by themselves and by other participants. Our participants expressed emotional intensity using gesture length, pressure, and speed primarily; the choice of attributes was impacted by the specific emotion, and the range and rate of increase of these attributes varied by individual and by emotion. Recognition accuracy of emotional intensity was higher at extreme ends, and was higher for one's own gestures than those made by others. The attributes of size and pressure (mapped to color in the animation) were most readily interpreted, while speed was more difficult to differentiate. We discuss human gesture drawing patterns to express emotional intensities and implications for developers of annotation systems and other touchscreen interfaces that wish to capture affect.

Gesture-typing is an efficient, easy-to-learn, and errortolerant technique for entering text on software keyboards. Our goal is to "recycle" users' otherwise-unused gesture variation to create rich output under the users' control, without sacrificing accuracy. Experiment 1 reveals a high level of existing gesture variation, even for accurate text, and shows that users can consciously vary their gestures under different conditions. We designed an Expressive Keyboard for a smart phone which maps input gesture features identified in Experiment 1 to a continuous output parameter space, i.e. RGB color. Experiment 2 shows that users can consciously modify their gestures, while retaining accuracy, to generate specific colors as they gesture-type. Users are more successful when they focus on output characteristics (such as red) rather than input characteristics (such as curviness). We designed an app with a dynamic font engine that continuously interpolates between several typefaces, as well as controlling weight and random variation. Experiment 3 shows that, in the context of a more ecologically-valid conversation task, users enjoy generating multiple forms of rich output. We conclude with suggestions for how the Expressive Keyboard approach can enhance a wide variety of gesture recognition applications.