Publications

April 20, 2020

IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)

A recent approach to improving the robustness of sound localization in reverberant environments is based on pre-selection of time-frequency pixels that are dominated by direct sound. This approach is equivalent to applying a binary time-frequency mask prior to the localization stage. Although the binary mask approach was shown to be effective, it may not exploit the information available in the captured signal to its full extent. In an attempt to overcome this limitation, it is hereby proposed to employ a soft mask instead of the binary mask.

Areas: AR/VR Machine Learning

January 1, 2020

Ethics in Design and Communication

Virtual Reality (VR) designers accept the ethical responsibilities of removing a user’s entire world and superseding it with a fabricated reality. These unique immersive design challenges are intensified when virtual experiences become public and socially-driven. As female VR designers in 2018, we see an opportunity to fold the language of consent into the design practice of virtual reality—as a means to design safe, accessible, virtual spaces.

Publication will be made available in 2020.

Areas: AR/VR Human Computer Interaction & UX

December 16, 2019

IEEE Journal of Selected Topics in Signal Processing

Virtual Reality (VR) and its applications have attracted significant and increasing attention. However, the requirements of much larger file sizes, different storage formats, and immersive viewing conditions pose significant challenges to the goals of acquiring, transmitting, compressing and displaying high quality VR content. Towards meeting these challenges, it is important to be able to understand the distortions that arise and that can affect the perceived quality of displayed VR content. It is also important to develop ways to automatically predict VR picture quality. Meeting these challenges requires basic tools in the form of large, representative subjective VR quality databases on which VR quality models can be developed and which can be used to benchmark VR quality prediction algorithms. Towards making progress in this direction, here we present the results of an immersive 3D subjective image quality assessment study.

Areas: AR/VR

December 15, 2019

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT)

One of the challenges in the field of haptics is to provide meaningful and realistic sensations to users. While most real world tactile sensations are composed of multiple dimensions, most commercial product only include vibration as it is the most cost effective solution. To improve on this, we introduce VPS (Vibration, Pressure, Shear) display, a multi-dimensional tactile array that increases information transfer by combining Vibration, Pressure, and Shear similar to how RGB LED combines red, blue, and green to create new colors.

Areas: AR/VR

December 15, 2019

IEEE Transactions on Haptics

We present experimental results that demonstrate that rendering haptic cues with multi-sensory components—specifically, lateral skin stretch, radial squeeze, and vibrotactile stimuli—improved perceptual distinguishability in comparison to similar cues with all-vibrotactile components. These results support the incorporation of diverse stimuli, both vibrotactile and non-vibrotactile, for applications requiring large haptic cue sets.

Areas: AR/VR

December 1, 2019

IEEE Transactions on Audio, Speech, and Language Processing (TASLP)

In this paper, a new method for pre-processing HRTFs in order to reduce their effective order is presented. The method uses phase-correction based on ear alignment, by exploiting the dual-centering nature of HRTF measurements. In contrast to time-alignment, the phase-correction is performed parametrically, making it more robust to measurement noise. The SH order reduction and ensuing interpolation errors due to sparse sampling were analyzed for these two methods.

Areas: AR/VR

November 18, 2019

ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia

Foveated rendering and compression can save computations by reducing the image quality in the peripheral vision. However, this can cause noticeable artifacts in the periphery, or, if done conservatively, would provide only modest savings. In this work, we explore a novel foveated reconstruction method that employs the recent advances in generative adversarial neural networks.

Areas: AR/VR Machine Learning

November 10, 2019

SIGGRAPH Asia

Designing a fully integrated 360◦ video camera supporting 6DoF head motion parallax requires overcoming many technical hurdles, including camera placement, optical design, sensor resolution, system calibration, real-time video capture, depth reconstruction, and real-time novel view synthesis. While there is a large body of work describing various system components, such as multi-view depth estimation, our paper is the first to describe a complete, reproducible system that considers the challenges arising when designing, building, and deploying a full end-to-end 6DoF video camera and playback environment.

Areas: AR/VR Computer Vision

November 9, 2019

Conference on Computer-Supported Cooperative Work and Social Computing (CSCW)

In immersive virtual reality (VR) environments, experiences of harassment can be exacerbated by features such as synchronous voice chat, heightened feelings of presence and embodiment, and avatar movements that can feel like violations of personal space (such as simulated touching or grabbing). Simultaneously, efforts to govern these developing spaces are made more complex by the distributed landscape of virtual reality applications and the dynamic nature of local community norms. To better understand this nascent social and psychological environment, we interviewed VR users (n=25) about their experiences with harassment, abuse, and discomfort in social VR.

Areas: AR/VR Human Computer Interaction & UX

October 29, 2019

International Conference on Computer Vision (ICCV)

We present a 16.2 million frame (50 hour) multimodal dataset of two-person face-to-face spontaneous conversations. Our dataset features synchronized body and finger motion as well as audio data. To the best of our knowledge, it represents the largest motion capture and audio dataset of natural conversations to date.

Areas: AR/VR Computer Vision Machine Learning