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A Survey on Ontologies for Human Behaviour Recognition

Natalia Díaz Rodríguez, Manuel Pegalajar Cuéllar, Johan Lilius, Miguel Delgado Calvo-Flores, A Survey on Ontologies for Human Behaviour Recognition. ACM Computing Surveys 46(4), 1–32, 2014.

Abstract:

Describing user activity plays an essential role on Ambient Intelligence. In this work, we review different methods for human activity recognition, classified as data-driven and knowledge-based techniques. We focus in context ontologies whose ultimate goal is the tracking of human behaviour. After studying upper and domain ontologies, both useful for human activity representation and inference, we establish an evaluation criterion to assess the suitability of the different candidate ontologies for this purpose. As a result, any missing features, which are relevant for modelling daily human behaviours, are identified as future challenges.

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BibTeX entry:

@ARTICLE{jDxPeLiDe13a,
  title = {A Survey on Ontologies for Human Behaviour Recognition},
  author = {Díaz Rodríguez, Natalia and Pegalajar Cuéllar, Manuel and Lilius, Johan and Delgado Calvo-Flores, Miguel},
  journal = {ACM Computing Surveys},
  volume = {46},
  number = {4},
  publisher = {ACM},
  pages = {1–32},
  year = {2014},
  keywords = {Human Behaviour Recognition, Activity Recognition, Context- Awareness, Ontologies},
}

Belongs to TUCS Research Unit(s): Embedded Systems Laboratory (ESLAB)

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