Human Motion Prediction Based on Object Interactions

Bruckschen, Lilli; Dengler, Nils; Bennewitz, Maren

doi:10.1109/ecmr.2019.8870963

Cited by 7 publications

(1 citation statement)

References 14 publications

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“…This would allow application of the planning-based methods in unknown environments. In addition, semantic indicators of possible goals, coming from understanding the person’s social role or current activity (Bruckschen et al, 2019), could lead to more robust intention recognition.…”

Section: Discussionmentioning

confidence: 99%

Human motion trajectory prediction: a survey

Rudenko

Palmieri

Herman³

et al. 2020

The International Journal of Robotics Research

527

306

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With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand, and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots, and advanced surveillance systems. This article provides a survey of human motion trajectory prediction. We review, analyze, and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.

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Section: Discussionmentioning

confidence: 99%