Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS

Understand

Estimating 3D poses of multiple humans in real-time is a classic but still challenging task in computer vision.

• Its major difficulty lies in the ambiguity in cross-view association of 2D poses and the huge state space when there are multiple people in multiple views.
• In this paper, we present a novel solution for multi-human 3D pose estimation from multiple calibrated camera views.
• It takes 2D poses in different camera coordinates as inputs and aims for the accurate 3D poses in the global coordinate.