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While the voxel-based methods have achieved promising results formulti-person 3D pose estimation from multi-cameras, they suffer from heavycomputation burdens, especially for large scenes. We present Faster VoxelPoseto address the challenge by re-projecting the feature volume to the threetwo-dimensional coordinate planes and estimating X, Y, Z coordinates from themseparately. To that end, we first localize each person by a 3D bounding box byestimating a 2D box and its height based on the volume features projected tothe xy-plane and z-axis, respectively. Then for each person, we estimatepartial joint coordinates from the three coordinate planes separately which arethen fused to obtain the final 3D pose. The method is free from costly 3D-CNNsand improves the speed of VoxelPose by ten times and meanwhile achievescompetitive accuracy as the state-of-the-art methods, proving its potential inreal-time applications.

Faster VoxelPose: Real-time 3D Human Pose Estimation by Orthographic Projection