Research Area
Year Published

44 Results

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

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 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
June 18, 2018

Eye In-Painting with Exemplar Generative Adversarial Networks

Computer Vision and Pattern Recognition (CVPR)

This paper introduces a novel approach to in-painting where the identity of the object to remove or change is preserved and accounted for at inference time: Exemplar GANs (ExGANs). ExGANs are a type of conditional GAN that utilize exemplar information to produce high-quality, personalized in-painting results.

By: Brian Dolhansky, Cristian Canton Ferrer
June 18, 2018

Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies

Computer Vision and Pattern Recognition (CVPR)

We present a unified deformation model for the markerless capture of human movement at multiple scales, including facial expressions, body motion, and hand gestures.

By: Hanbyul Joo, Tomas Simon, Yaser Sheikh
June 18, 2018

Audio to Body Dynamics

Computer Vision and Pattern Recognition (CVPR)

We present a method that gets as input an audio of violin or piano playing, and outputs a video of skeleton predictions which are further used to animate an avatar. The key idea is to create an animation of an avatar that moves their hands similarly to how a pianist or violinist would do, just from audio.

By: Eli Shlizerman, Lucio Dery, Hayden Schoen, Ira Kemelmacher Shlizerman