Estimating Human Dynamics On-the-fly Using Monocular Video For Pose Estimation

摘要

Human pose estimation using uncalibrated monocular visual inputs alone is a challenging problem for both the computer vision and robotics communities. From the robotics perspective, the challenge here is one of pose estimation of a multiply-articulated system of bodies using a single nonspecialized environmental sensor (the camera) and thereby, creating low-order surrogate computational models for analysis and control.