Improve human motion estimate in video using physics with HUND+SO+GT+Dynamics

Improve human motion estimate in video using physics with HUND+SO+GT+Dynamics

Trajectory Optimization for Physics-Based Reconstruction of 3d Human Pose from Monocular Video

arXiv paper abstract https://arxiv.org/abs/2205.12292

arXiv PDF paper https://arxiv.org/pdf/2205.12292.pdf

... the task of estimating a physically plausible articulated human motion from monocular video.

Existing approaches that do not consider physics often produce temporally inconsistent output with motion artifacts, while state-of-the-art physics-based approaches have either been shown to work only in controlled laboratory conditions or consider simplified body-ground contact limited to feet.

... shortcomings can be addressed by directly incorporating a fully-featured physics engine into the pose estimation process.

Given ... real-world ... input ... estimates the ground-plane location and the dimensions of the physical body model ... recovers the physical motion by performing trajectory optimization.

... generalizes to a variety of scenes that might have diverse ground properties and supports any form of self-contact and contact between the articulated body and scene geometry.

... competitive results with respect to existing physics-based methods ... while ... applicable without re-training to more complex dynamic motions ...

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