A hybrid framework for online recognition of activities of daily living in real-world settings

AVSS, pp. 37-43, 2016.

Cited by: 2|Bibtex|Views18
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Other Links: dblp.uni-trier.de|academic.microsoft.com

Abstract:

Many supervised approaches report state-of-the-art results for recognizing short-term actions in manually clipped videos by utilizing fine body motion information. The main downside of these approaches is that they are not applicable in real world settings. The challenge is different when it comes to unstructured scenes and long-term vide...More

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