Search Results for author:
Found 10 papers, 5 papers with code
Ultra Inertial Poser: Scalable Motion Capture and Tracking from Sparse Inertial Sensors and Ultra-Wideband Ranging
Our method then fuses these inter-sensor distances with the 3D states estimated from each sensor Our graph-based machine learning model processes the 3D states and distances to estimate a person's 3D full body pose and translation.
How Suboptimal is Training rPPG Models with Videos and Targets from Different Body Sites?
Using a recently released unique dataset with synchronized contact PPG and video measurements from both the hand and face, we can provide precise and quantitative answers to this question.
Representation Learning for Wearable-Based Applications in the Case of Missing Data
We further investigate the impact of imputation strategies and masking rations on downstream classification tasks.
Video-based sympathetic arousal assessment via peripheral blood flow estimation
We obtain median correlations of 0. 57 to 0. 63 between our inferred signals and the ground truth EDA using only videos of the participants' palms or foreheads or PPG signals from the foreheads or fingers.
Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning
The success of contrastive learning is well known to be dependent on data augmentation.
EgoPoser: Robust Real-Time Ego-Body Pose Estimation in Large Scenes
Full-body ego-pose estimation from head and hand poses alone has become an active area of research to power articulate avatar representation on headset-based platforms.
BeliefPPG: Uncertainty-aware Heart Rate Estimation from PPG signals via Belief Propagation
We present a novel learning-based method that achieves state-of-the-art performance on several heart rate estimation benchmarks extracted from photoplethysmography signals (PPG).
Heart rate estimation
Photoplethysmography (PPG) heart rate estimation
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Restore Anything Pipeline: Segment Anything Meets Image Restoration
In this paper, we introduce the Restore Anything Pipeline (RAP), a novel interactive and per-object level image restoration approach that incorporates a controllable model to generate different results that users may choose from.
HOOV: Hand Out-Of-View Tracking for Proprioceptive Interaction using Inertial Sensing
In this paper, we present HOOV, a wrist-worn sensing method that allows VR users to interact with objects outside their field of view.
AvatarPoser: Articulated Full-Body Pose Tracking from Sparse Motion Sensing
In this paper, we present AvatarPoser, the first learning-based method that predicts full-body poses in world coordinates using only motion input from the user's head and hands.
