Teleportation, which instantly moves users from their current location to the target location, has become the most popular locomotion technique in VR games. It enables fast navigation with reduced VR sickness but results in significantly reduced immersion. We present HeadWind, a novel approach to improve the experience of teleportation by simulating the haptic sensation of air drag when rapidly moving through the air in real life. Specifically, HeadWind modulates bursts of compressed air to the face and uses multiple nozzles to provide directional cues. To design the wearable device and to model airflow speed and duration for teleportation, we conducted three formative studies and a design session. User experience evaluation with 24 participants showed that HeadWind significantly improved realism, immersion, and enjoyment of teleportation in VR (p<.01) with large effect sizes (r>0.5), and was preferred by 96% of participants.

Haptic feedback significantly enhances virtual experiences. However, supporting haptics currently requires modifying the codebase, making it impractical to add haptics to popular, high-quality experiences such as best selling games, which are typically closed-source. We present HapticSeer, a multi-channel, black-box, platform-agnostic approach to detecting game events for real-time haptic feedback. The approach is based on two key insights: 1) all games have 3 types of data streams: video, audio, and controller I/O, that can be analyzed in real-time to detect game events, and 2) a small number of user interface design patterns are reused across most games, so that event detectors can be reused effectively. We developed an open-source HapticSeer framework and implemented several real-time event detectors for commercial PC and VR games. We validated system correctness and real-time performance, and discuss feedback from several haptics developers that used the HapticSeer framework to integrate research and commercial haptic devices.

JetController is a novel haptic technology capable of supporting high-speed and persistent 3-DoF ungrounded force feedback. It uses high-speed pneumatic solenoid valves to modulate compressed air to achieve 20-50Hz of full impulses at 4.0-1.0N, and combines multiple air propulsion jets to generate 3-DoF force feedback. Compared to propeller-based approaches, JetController supports 10-30 times faster impulse frequency, and its handheld device is significantly lighter and more compact. JetController supports a wide range of haptic events in games and VR experiences, from firing automatic weapons in games like Halo (15Hz) to slicing fruits in Fruit Ninja (up to 45Hz). To evaluate JetController, we integrated our prototype with two popular VR games, Half-life: Alyx and Beat Saber, to support a variety of 3D interactions. Study results showed that JetController significantly improved realism, enjoyment, and overall experience compared to commercial vibrating controllers, and was preferred by most participants.

We present Miniature Haptics, a new approach to providing realistic haptic experiences by applying miniaturized haptic feedback to hand-based, embodied avatars. By shrinking haptics to a much smaller scale, Miniature Haptics enables the exploration of new haptic experiences that are not practical to create at the full, human-body scale. Using Finger Walking in Place (FWIP) as an example avatar embodiment and control method, we first explored the feasibility of Miniature Haptics then conducted a human factors study to understand how people map their full-body skeletal model to their hands. To understand the user experience of Miniature Haptic, we developed a miniature football haptic display, and results from our user study show that Miniature Haptics significantly improved the realism and enjoyment of the experience and is preferred by users (p < 0.05). In addition, we present two miniature motion platforms supporting the haptic experiences of: 1) rapidly changing ground height for platform jumping games such as Super Mario Bros and 2) changing terrain slope. Overall, Miniature Haptics makes it possible to explore novel haptic experiences that have not been practical before.

A common joint source-channel (JSC) decoder structure for predictively encoded sources involves first forming a JSC decoding estimate of the prediction residual and then feeding this estimate to a standard predictive decoding (synthesis) filter. In this paper, we demonstrate that in a JSC decoding context, use of this standard filter is suboptimal. In place of the standard filter, we choose the synthesis filter coefficients to give a least-squares (LS) estimate of the original source, based on given training data. For first-order differential pulse-code modulation, this yields as much as 0.65-dB gain in reconstructing first-order Gauss-Markov sources. More gains are achieved with modest additional complexity by increasing the filter order. While performance can also be enhanced by increasing the source's Markov model order and/or the decoder's lookup table memory, complexity grows exponentially in these parameters. For both predictive and nonpredictive coding, our LS approach offers a strategy for increasing the estimation accuracy of JSC decoders while retaining manageable complexity.