Elia Bonetto — accepted AI-conference papers

2022

AirPose: Multi-View Fusion Network for Aerial 3D Human Pose and Shape Estimation

Nitin Saini, Elia Bonetto, Eric Price, Aamir Ahmad, Michael J. Black

RA-L 2022

In this letter, we present a novel markerless 3D human motion capture (MoCap) system for unstructured, outdoor environments that uses a team of autonomous unmanned aerial vehicles (UAVs) with on-board RGB cameras and computation. Existing methods are limited by calibrated cameras and off-line proces

Cited by 32 Source ↗code ↗Scholar ↗

2020

AirCapRL: Autonomous Aerial Human Motion Capture Using Deep Reinforcement Learning

Rahul Tallamraju, Nitin Saini, Elia Bonetto, Michael Pabst, Yu Tang Liu, Michael J. Black +1

RA-L 2020

In this letter, we introduce a deep reinforcement learning (RL) based multi-robot formation controller for the task of autonomous aerial human motion capture (MoCap). We focus on vision-based MoCap, where the objective is to estimate the trajectory of body pose and shape of a single moving person us

Cited by 33 Source ↗Scholar ↗