Natalia Díaz Rodríguez
M. P. Cuéllar
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Abstract
Describing user activity plays an essential role in ambient intelligence. In this work, we review different methods for human activity recognition, classified as data-driven and knowledge-based techniques. We focus on context ontologies whose ultimate goal is the tracking of human behavior. 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 modeling daily human behaviors, are identified as future challenges.
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- Huiyu Zhou and Huosheng Hu. 2008. Human motion tracking for rehabilitation, a survey. Biomedical Signal Processing and Control 3, 1 (2008), 1--18.Google ScholarCross Ref
Index Terms
- A survey on ontologies for human behavior recognition
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