SimpleEgo: Predicting Probabilistic Body Pose from Egocentric Cameras

Understand

Our work addresses the problem of egocentric human pose estimation from downwards-facing cameras on head-mounted devices (HMD).

• This presents a challenging scenario, as parts of the body often fall outside of the image or are occluded.
• Previous solutions minimize this problem by using fish-eye camera lenses to capture a wider view, but these can present hardware design issues.
• They also predict 2D heat-maps per joint and lift them to 3D space to deal with self-occlusions, but this requires large network architectures which are impractical to deploy on resource-constrained HMDs.