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

@article{Schreiter2022TheMH,
  title={The Magni Human Motion Dataset: Accurate, Complex, Multi-Modal, Natural, Semantically-Rich and Contextualized},
  author={Tim Schreiter and Tiago Rodrigues de Almeida and Yufei Zhu and Eduardo Gutierrez Maestro and Lucas Morillo-M{\'e}ndez and Andrey Rudenko and Tomasz Piotr Kucner and {\'O}scar Mart{\'i}nez Mozos and Martin Magnusson and Luigi Palmieri and Kai Oliver Arras and Achim J. Lilienthal},
  journal={ArXiv},
  year={2022},
  volume={abs/2208.14925}
}
—Rapid development of social robots stimulates active research in human motion modeling, interpretation and prediction, proactive collision avoidance, human-robot interac- tion and co-habitation in shared spaces. Modern approaches to this end require high quality datasets of human motion trajectories 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… 

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