Research Area
Year Published

89 Results

September 3, 2018

QuaterNet: A Quaternion-based Recurrent Model for Human Motion

British Machine Vision Convention (BMVC)

Deep learning for predicting or generating 3D human pose sequences is an active research area. Previous work regresses either joint rotations or joint positions. The former strategy is prone to error accumulation along the kinematic chain, as well as discontinuities when using Euler angle or exponential map parameterizations. The latter requires re-projection onto skeleton constraints to avoid bone stretching and invalid configurations. This work addresses both limitations.

By: Dario Pavllo, David Grangier, Michael Auli

August 26, 2018

Designing Variable Stiffness Profiles To Optimize The Physical Human Robot Interface Of Hand Exoskeletons

The 7th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics

The design of comfortable and effective physical human robot interaction (pHRI) interfaces for force transfer is a prominent challenge for coupled human-robot systems. Forces applied by the robot at the fingers create reaction forces on the dorsal surface of the hand, often leading to high pressure concentrations which can cause pain and discomfort. In this paper, the interaction between the pHRI interface and the dorsal surface of the hand is systematically characterized, and a new method for the design of comfortable interfaces is presented.

By: Rohit John Varghese, Gaurav Mukherjee, Raymond King, Sean Keller, Ashish D. Deshpande

August 21, 2018

SE-Sync: A certifiably correct algorithm for synchronization over the special Euclidean group

International Journal of Robotics Research

Many important geometric estimation problems naturally take the form of synchronization over the special Euclidean group: estimate the values of a set of unknown group elements x1, . . . , xn ∈ SE(d) given noisy measurements of a subset of their pairwise relative transforms xi−1xj. Examples of this class include the foundational problems of pose-graph simultaneous localization and mapping (SLAM) (in robotics), camera motion estimation (in computer vision), and sensor network localization (in distributed sensing), among others. This inference problem is typically formulated as a nonconvex maximum-likelihood estimation that is computationally hard to solve in general. Nevertheless, in this paper we present an algorithm that is able to efficiently recover certifiably globally optimal solutions of the special Euclidean synchronization problem in a non-adversarial noise regime.

By: David M. Rosen, Luca Carlone, Afonso S. Bandeira, John J. Leonard

August 14, 2018

Deep Appearance Models for Face Rendering

ACM SIGGRAPH

We introduce a deep appearance model for rendering the human face. Inspired by Active Appearance Models, we develop a data-driven rendering pipeline that learns a joint representation of facial geometry and appearance from a multiview capture setup.

By: Stephen Lombardi, Jason Saragih, Tomas Simon, Yaser Sheikh

August 10, 2018

Effects of virtual acoustics on target-word identification performance in multi-talker environments

ACM Symposium on Applied Perception (SAP)

Many virtual reality applications let multiple users communicate in a multi-talker environment, recreating the classic cocktail-party effect. While there is a vast body of research focusing on the perception and intelligibility of human speech in real-world scenarios with cocktail party effects, there is little work in accurately modeling and evaluating the effect in virtual environments.

By: Atul Rungta, Nicholas Rewkowski, Carl Schissler, Philip Robinson, Ravish Mehra, Dinesh Manocha
Areas: AR/VR

August 10, 2018

Learning to Feel Words: A Comparison of Learning Approaches to Acquire Haptic Words

ACM Symposium on Applied Perception (SAP)

Recent studies have shown that decomposing spoken or written language into phonemes and transcribing each phoneme into a unique vibrotactile pattern enables people to receive lexical messages on the arm. A potential barrier to adopting this new communication system is the time and effort required to learn the association between phonemes and vibrotactile patterns. Therefore, in this study, we compared the learnability and generalizability of different learning approaches, including guided learning, self-directed learning, and a mnemonic device.

By: Jennifer Chen, Robert Turcott, Pablo Castillo, Wahyudinata Setiawan, Frances Lau, Ali Israr
Areas: AR/VR

July 30, 2018

Instant 3D Photography

SIGGRAPH

We present an algorithm for constructing 3D panoramas from a sequence of aligned color-and-depth image pairs. Such sequences can be conveniently captured using dual lens cell phone cameras that reconstruct depth maps from synchronized stereo image capture.

By: Peter Hedman, Johannes Kopf

July 29, 2018

Online Optical Marker-based Hand Tracking with Deep Labels

Special Interest Group on Computer Graphics and Interactive Techniques (SIGGRAPH)

We propose a technique that frames the labeling problem as a keypoint regression problem conducive to a solution using convolutional neural networks.

By: Shangchen Han, Beibei Liu, Robert Wang, Yuting Ye, Christopher D. Twigg, Kenrick Kin

July 7, 2018

Reconstructing Scenes with Mirror and Glass Surfaces

ACM SIGGRAPH

We introduce a fully automatic pipeline that allows us to reconstruct the geometry and extent of planar glass and mirror surfaces while being able to distinguish between the two.

By: Thomas Whelan, Michael Goesele, Steven J. Lovegrove, Julian Straub, Simon Green, Richard Szeliski, Steven Butterfield, Shobhit Verma, Richard Newcombe

July 6, 2018

DeepFocus: Learned Image Synthesis for Computational Display

ACM SIGGRAPH (Talks Program)

In this paper, we introduce Deep-Focus, a generic, end-to-end trainable convolutional neural network designed to efficiently solve the full range of computational tasks for accommodation-supporting HMDs.

By: Lei Xiao, Anton Kaplanyan, Alexander Fix, Matt Chapman, Douglas Lanman