Scene-aware Egocentric 3D Human Pose Estimation

Understand

Egocentric 3D human pose estimation with a single head-mounted fisheye camera has recently attracted attention due to its numerous applications in virtual and augmented reality.

• Existing methods still struggle in challenging poses where the human body is highly occluded or is closely interacting with the scene.
• To address this issue, we propose a scene-aware egocentric pose estimation method that guides the prediction of the egocentric pose with scene constraints.
• To this end, we propose an egocentric depth estimation network to predict the scene depth map from a wide-view egocentric fisheye camera while mitigating the occlusion of the human body with a depth-inpainting network.