RICA: Robocentric Indoor Crowd Analysis Dataset

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


In this paper, 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.
Original languageEnglish
Title of host publicationUKRAS20 Conference: “Robots into the real world” Proceedings
Publication statusPublished - 2020


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