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ActiveMoCap: Optimized Viewpoint Selection for Active Human Motion Capture

CVPR 2020 · 3D vision › Human pose estimation · approach: Physics and sensor-based motion capture · 37 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
choose camera viewpoints by minimizing predicted pose uncertaintyActiveMoCap · Teleportation, total3D pose error: 0.195±0.07 -> 0.144±0.35; 0.216±0.06 -> 0.144±0.35Helped
choose camera viewpoints by minimizing predicted pose uncertaintyActiveMoCap · MPI-INF-3DHP, teleportation (networks)3D pose error: 0.28±0.03 -> 0.21±0.0008; 0.29±0.03 -> 0.21±0.0008Helped
choose camera viewpoints by minimizing predicted pose uncertaintyActiveMoCap · MPI-INF-3DHP, teleportation (noisy ground truth)3D pose error: 0.286±0.027 -> 0.145±0.006; 0.265±0.010 -> 0.145±0.006Helped
use uncertainty-based active viewpoint selection rather than constant rotationActiveMoCap · Drone flight, total3D pose error: 0.30±0.08 -> 0.31±0.10No clear effect
use uncertainty-based active viewpoint selection rather than random movementActiveMoCap · Drone flight, total3D pose error: 0.62±0.15 -> 0.31±0.10Helped
add a drone flight model to predict future camera positions (ablation)ActiveMoCap · CMU-Dribble, CMU-Sitting, CMU-Dinosour; drone flight3D pose error: 0.65±0.09 -> 0.28±0.006; 0.48±0.09 -> 0.15±0.007; 0.22±0.07 -> 0.12±0.02Helped
add a drone flight model to predict future camera positions (ablation)ActiveMoCap · Drone flight, total (ablation study)3D pose error: 0.45±0.08 -> 0.18±0.01Helped

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