Deep Semantic Abstractions of Everyday Human Activities (bibtex)
by Jakob Suchan, Mehul Bhatt
Abstract:
We propose a deep semantic characterisation of space and motion categorically from the viewpoint of grounding embodied human-object interactions. Our key focus is on an ontological model that would be adept to formalisation from the viewpoint of commonsense knowledge representation, relational learning, and qualitative reasoning about space and motion in cognitive robotics settings. We demonstrate key aspects of the space & motion ontology and its formalisation as a representational framework in the backdrop of select examples from a dataset of everyday activities. Furthermore, focussing on human-object interaction data obtained from RGBD sensors, we also illustrate how declarative (spatio-temporal) reasoning in the (constraint) logic programming family may be performed with the developed deep semantic abstractions.
Reference:
Jakob Suchan, Mehul Bhatt, "Deep Semantic Abstractions of Everyday Human Activities", In ROBOT 2017: Third Iberian Robotics Conference, Springer International Publishing, Cham, pp. 477-488, 2018.
Bibtex Entry:
@InProceedings{10.1007/978-3-319-70833-1_39,
author="Suchan, Jakob
and Bhatt, Mehul",
editor="Ollero, Anibal
and Sanfeliu, Alberto
and Montano, Luis
and Lau, Nuno
and Cardeira, Carlos",
title="Deep Semantic Abstractions of Everyday Human Activities",
booktitle="ROBOT 2017: Third Iberian Robotics Conference",
year="2018",
publisher="Springer International Publishing",
address="Cham",
pages="477--488",
abstract="We propose a deep semantic characterisation of space and motion categorically from the viewpoint of grounding embodied human-object interactions. Our key focus is on an ontological model that would be adept to formalisation from the viewpoint of commonsense knowledge representation, relational learning, and qualitative reasoning about space and motion in cognitive robotics settings. We demonstrate key aspects of the space {\&} motion ontology and its formalisation as a representational framework in the backdrop of select examples from a dataset of everyday activities. Furthermore, focussing on human-object interaction data obtained from RGBD sensors, we also illustrate how declarative (spatio-temporal) reasoning in the (constraint) logic programming family may be performed with the developed deep semantic abstractions.",
isbn="978-3-319-70833-1",
keywords={easecrc_knowledge}
}
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