ロボット視点からの3D人体姿勢推定と予測：HARPERデータセット
Exploring 3D Human Pose Estimation and Forecasting from the Robot's Perspective: The HARPER Dataset
四足歩行ロボットSpotと人間の相互作用をロボット搭載カメラで撮影したデータセットHARPERを構築し、3D姿勢推定・予測・衝突予測のベンチマークを提供した。
著者: Andrea Avogaro, Andrea Toaiari, Federico Cunico, Xiangmin Xu, Haralambos Dafas, Alessandro Vinciarelli, Emma Li, Marco Cristani
分類: cs.CV, cs.RO
原文アブストラクト
We introduce HARPER, a novel dataset for 3D body pose estimation and forecast in dyadic interactions between users and Spot, the quadruped robot manufactured by Boston Dynamics. The key-novelty is the focus on the robot's perspective, i.e., on the data captured by the robot's sensors. These make 3D body pose analysis challenging because being close to the ground captures humans only partially. The scenario underlying HARPER includes 15 actions, of which 10 involve physical contact between the robot and users. The Corpus contains not only the recordings of the built-in stereo cameras of Spot, but also those of a 6-camera OptiTrack system (all recordings are synchronized). This leads to ground-truth skeletal representations with a precision lower than a millimeter. In addition, the Corpus includes reproducible benchmarks on 3D Human Pose Estimation, Human Pose Forecasting, and Collision Prediction, all based on publicly available baseline approaches. This enables future HARPER users to rigorously compare their results with those we provide in this work.
