Mocap Everyone Everywhere: Lightweight Motion Capture with Smartwatches and a Head-Mounted Camera
Jiye Lee, Hanbyul Joo
摘要
We present a lightweight and affordable motion capture method based on two smartwatches and a head-mounted camera. In contrast to the existing approaches that use six or more expert-level IMU devices, our approach is much more cost-effective and convenient. Our method can make wearable motion capture accessible to everyone every-where, enabling 3D full-body motion capture in diverse environments. As a key idea to overcome the extreme sparsity and ambiguities of sensor inputs with different modalities, we integrate 6D head poses obtained from the head-mounted cameras for motion estimation. To enable capture in expansive indoor and outdoor scenes, we propose an algorithm to track and update floor level changes to define head poses, coupled with a multi-stage Transformer-based regression module. We also introduce novel strategies leveraging visual cues of egocentric images to further enhance the motion capture quality while reducing ambi-guities. We demonstrate the performance of our method on various challenging scenarios, including complex outdoor environments and everyday motions including object inter-actions and social interactions among multiple individuals.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper16
- MobilePoser: Real-Time Full-Body Pose Estimation and 3D Human Translation from IMUs in Mobile Consumer DevicesVasco Xu, Chenfeng Gao, Henry Hoffmann, Karan AhujaUIST 2024 · 被引用 37 次
- GENMO: A GENeralist Model for Human MOtionJiefeng Li, Jinkun Cao, Haotian Zhang, Davis Rempe 等ICCV 2025 · 被引用 15 次
- RAM: Recover Any 3D Human Motion in-the-WildSen Jia, Ning Zhu, Jinqin Zhong, Jiale Zhou 等CVPR 2026 · 被引用 12 次
- Improving Global Motion Estimation in Sparse IMU-based Motion Capture with PhysicsXinyu Yi, Shaohua Pan, Feng XuSIGGRAPH 2025 · 被引用 7 次
- Ground Reaction Inertial Poser: Physics-based Human Motion Capture from Sparse IMUs and Insole Pressure SensorsRyosuke Hori, Jyun-Ting Song, Zhengyi Luo, Jinkun Cao 等CVPR 2026 · 被引用 2 次
它引用的顶会 Paper25
- AMASS: Archive of Motion Capture As Surface ShapesNaureen Mahmood, Nima Ghorbani, Nikolaus F. Troje, Gerard Pons-Moll 等ICCV 2019 · 被引用 1,784 次
- DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D CamerasZachary Teed, Jia DengNeurIPS 2021 · 被引用 1,248 次
- Humans in 4D: Reconstructing and Tracking Humans with TransformersShubham Goel, Georgios Pavlakos, Jathushan Rajasegaran, Angjoo Kanazawa 等ICCV 2023 · 被引用 390 次
- TransPose: real-time 3D human translation and pose estimation with six inertial sensorsXinyu Yi, Yuxiao Zhou, Feng XuSIGGRAPH 2021 · 被引用 200 次
- Physical Inertial Poser (PIP): Physics-aware Real-time Human Motion Tracking from Sparse Inertial SensorsXinyu Yi, Yuxiao Zhou, Marc Habermann, Soshi Shimada 等CVPR 2022 · 被引用 198 次
相关 Paper
- BaroPoser: Real-time Human Motion Tracking from IMUs and Barometers in Everyday DevicesLibo Zhang, Xinyu Yi, Feng XuUIST 2025 · 被引用 1 次
- Mobile. Egocentric Human Body Motion Reconstruction Using Only Eyeglasses-mounted Cameras and a Few Body-worn Inertial SensorsYoung-Woon Cha, Husam Shaik, Qian Zhang, Fan Feng 等IEEE VR 2021 · 被引用 15 次
- UltraPoser: Pushing the Limits of IMU-based Full-Body Pose Estimation with Ultrasound Sensing on Consumer WearablesYadong Li, Shuning Wang, Yongjian Fu, Justin Chen 等UIST 2025 · 被引用 2 次
- FRAME: Floor-aligned Representation for Avatar Motion from Egocentric VideoAndrea Boscolo Camiletto, Jian Wang, Eduardo Alvarado, Rishabh Dabral 等CVPR 2025
- Ego4o: Egocentric Human Motion Capture and Understanding from Multi-Modal InputJian Wang, Rishabh Dabral, Diogo C. Luvizon, Zhe Cao 等CVPR 2025
