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We introduce a novel task of reconstructing a time series of second-person 3Dhuman body meshes from monocular egocentric videos. The unique viewpoint andrapid embodied camera motion of egocentric videos raise additional technicalbarriers for human body capture. To address those challenges, we propose asimple yet effective optimization-based approach that leverages 2D observationsof the entire video sequence and human-scene interaction constraint to estimatesecond-person human poses, shapes, and global motion that are grounded on the3D environment captured from the egocentric view. We conduct detailed ablationstudies to validate our design choice. Moreover, we compare our method with theprevious state-of-the-art method on human motion capture from monocular video,and show that our method estimates more accurate human-body poses and shapesunder the challenging egocentric setting. In addition, we demonstrate that ourapproach produces more realistic human-scene interaction.

4D Human Body Capture from Egocentric Video via 3D Scene Grounding