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From Object Recognition to Activity Interpretation and Back, Based on Point Cloud Data

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Abstract

Semantic mapping of static environments has become a hot topic in robotics. The aim of the Mermaid project was to investigate the transfer of a sensor data interpretation approach for mapping to the problem of activity recognition in smart home applications such as elderly care. The basic structure of the semantic mapping approach, i.e., to assemble hypotheses of object aggregates in a closed-loop process of bottom-up raw data interpretation and top-down expectation generation from a domain ontology, can be extended to the temporal domain to include activity interpretation. This paper reports initial results, based on a study using point clouds from depth (RGB-D) sensor data.

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Acknowledgements

Work in the project Mermaid reported here was partially funded by BMBF (grant NZL 10/003) and the RSNZ (grant FRG10-11) under a bilateral research collaboration agreement. This is gratefully acknowledged.

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Authors and Affiliations

  1. Institute of Computer Science, Osnabrück University, Osnabrück, Germany

    Sven Albrecht, Thomas Wiemann & Joachim Hertzberg

  2. School of Engineering and Advanced Technology, Massey University, Wellington, New Zealand

    Hans W. Guesgen & Stephen Marsland

Authors
  1. Sven Albrecht
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  2. Thomas Wiemann
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  3. Joachim Hertzberg
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  4. Hans W. Guesgen
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  5. Stephen Marsland
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Correspondence to Sven Albrecht.

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Albrecht, S., Wiemann, T., Hertzberg, J. et al. From Object Recognition to Activity Interpretation and Back, Based on Point Cloud Data. Künstl Intell 27, 161–167 (2013). https://doi.org/10.1007/s13218-013-0244-5

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