4 papers
Distinguishing Imitation Error from Intrinsic Motion Learning Difficulty
Zhaorui Meng, Lu Yin, Xinrui Chen +4
Physics-based motion imitation is central to humanoid control, yet current evaluation metrics (e.g., MPJPE) only quantify imitation outcomes, not their underlying causes. This conf…
Transformer IMU Calibrator: Dynamic On-body IMU Calibration for Inertial Motion Capture
Chengxu Zuo, Jiawei Huang, Xiao Jiang +7
In this paper, we propose a novel dynamic calibration method for sparse inertial motion capture systems, which is the first to break the restrictive absolute static assumption in I…
FIP: Endowing Robust Motion Capture on Daily Garment by Fusing Flex and Inertial Sensors
Jiawei Fang, Ruonan Zheng, Yuanyao +4
What if our clothes could capture our body motion accurately? This paper introduces Flexible Inertial Poser (FIP), a novel motion-capturing system using daily garments with two elb…
SuDA: Support-based Domain Adaptation for Sim2Real Motion Capture with Flexible Sensors
Jiawei Fang, Haishan Song, Chengxu Zuo +4
Flexible sensors hold promise for human motion capture (MoCap), offering advantages such as wearability, privacy preservation, and minimal constraints on natural movement. However,…