40 citations · 122 across the 8 of their papers we have counts for
8 papers
SkelFormer: Markerless 3D Pose and Shape Estimation using Skeletal Transformers
Vandad Davoodnia, Saeed Ghorbani, Alexandre Messier +1
We introduce SkelFormer, a novel markerless motion capture pipeline for multi-view human pose and shape estimation. Our method first uses off-the-shelf 2D keypoint estimators, pre-…
UPose3D: Uncertainty-Aware 3D Human Pose Estimation with Cross-View and Temporal Cues
Vandad Davoodnia, Saeed Ghorbani, Marc-André Carbonneau +2
We introduce UPose3D, a novel approach for multi-view 3D human pose estimation, addressing challenges in accuracy and scalability. Our method advances existing pose estimation fram…
Human Pose Estimation from Ambiguous Pressure Recordings with Spatio-temporal Masked Transformers
Vandad Davoodnia, Ali Etemad
Despite the impressive performance of vision-based pose estimators, they generally fail to perform well under adverse vision conditions and often don't satisfy the privacy demands…
Estimating Pose from Pressure Data for Smart Beds with Deep Image-based Pose Estimators
Vandad Davoodnia, Saeed Ghorbani, Ali Etemad
In-bed pose estimation has shown value in fields such as hospital patient monitoring, sleep studies, and smart homes. In this paper, we explore different strategies for detecting b…
Identity and Posture Recognition in Smart Beds with Deep Multitask Learning
Vandad Davoodnia, Ali Etemad
Sleep posture analysis is widely used for clinical patient monitoring and sleep studies. Earlier research has revealed that sleep posture highly influences symptoms of diseases suc…
Deep Multitask Learning for Pervasive BMI Estimation and Identity Recognition in Smart Beds
Vandad Davoodnia, Monet Slinowsky, Ali Etemad
Smart devices in the Internet of Things (IoT) paradigm provide a variety of unobtrusive and pervasive means for continuous monitoring of bio-metrics and health information. Further…
In-bed Pressure-based Pose Estimation using Image Space Representation Learning
Vandad Davoodnia, Saeed Ghorbani, Ali Etemad
Recent advances in deep pose estimation models have proven to be effective in a wide range of applications such as health monitoring, sports, animations, and robotics. However, pos…
Auto-labelling of Markers in Optical Motion Capture by Permutation Learning
Saeed Ghorbani, Ali Etemad, Nikolaus F. Troje
Optical marker-based motion capture is a vital tool in applications such as motion and behavioural analysis, animation, and biomechanics. Labelling, that is, assigning optical mark…