The Magni Human Motion Dataset : Accurate, Complex, Multi-Modal, Natural, Semantically-Rich and Contextualized

Tim Schreiter, Tiago Rodrigues de Almeida, Yufei Zhu, Eduardo Gutiérrez Maestro, Lucas Morillo-Mendez, Andrey Rudenko, Tomasz P. Kucner, Oscar Martinez Mozos, Martin Magnusson, Luigi Palmieri, Kai O. Arras, Achim Lilienthal

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

Abstract

Rapid development of social robots stimulates active research in human motion modeling, interpretation and prediction, proactive collision avoidance, human-robot interaction and co-habitation in shared spaces. Modern approaches to this end require high quality datasets for training and evaluation. However, the majority of available datasets suffers from either inaccurate tracking data or unnatural, scripted behavior of the tracked people. This paper attempts to fill this gap by providing high quality tracking information from motion capture, eye-gaze trackers and on-board robot sensors in a semantically-rich environment. To induce natural behavior of the recorded participants, we utilise loosely scripted task assignment, which induces the participants navigate through the dynamic laboratory environment in a natural and purposeful way. The motion dataset, presented in this paper, sets a high quality standard, as the realistic and accurate data is enhanced with semantic information, enabling development of new algorithms which rely not only on the tracking information but also on contextual cues of the moving agents, static and dynamic environment. 
Original languageEnglish
Title of host publication31st IEEE International Conference on Robot & Human Interactive Communication
PublisherIEEE
Number of pages4
DOIs
Publication statusAccepted/In press - 2023
MoE publication typeA4 Conference publication
EventIEEE International Conference on Robot and Human Interactive Communication - Napoli, Italy
Duration: 29 Aug 20222 Sept 2022

Conference

ConferenceIEEE International Conference on Robot and Human Interactive Communication
Abbreviated titleRO-MAN
Country/TerritoryItaly
CityNapoli
Period29/08/202202/09/2022

Keywords

  • Dataset
  • Human Motion Prediction
  • Eye Tracking
  • Computer Sciences
  • Datavetenskap (datalogi)

Fingerprint

Dive into the research topics of 'The Magni Human Motion Dataset : Accurate, Complex, Multi-Modal, Natural, Semantically-Rich and Contextualized'. Together they form a unique fingerprint.

Cite this