RICA: Robocentric Indoor Crowd Analysis Dataset

Published in UKRAS20 Conference: “Robots into the real world” Proceedings

Viktor Schmuck Oya Celiktutan

Department of Engineering, King's College London

Abstract

We introduce an egocentric dataset recorded from a robot's point of view (robocentric), which has been created to serve as a platform for indoor crowd analysis. The dataset features over 100,000 RGB, depth, and wide-angle camera images as well as LIDAR readings, recorded during a social gathering where the robot captured group interactions between participants using its on-board sensors. We evaluated three different human detection algorithms on our dataset to demonstrate the challenges of indoor crowd analysis from a robot's perspective.

Paper: [PDF] Proceedings: [UKRAS20] Data: [Contact SAIR lab]

Bibtex

@article{SchmuckCeliktutanUKRAS20,
  title={RICA: Robocentric Indoor Crowd Analysis Dataset},
  author={Schmuck, Viktor and Celiktutan, Oya},
  journal={UKRAS20 Conference: “Robots into the real world” Proceedings},
  pages={63--65},
  year = {2020}
}