Semi-supervised understanding of complex activities from temporal concepts

AVSS, pp. 80-87, 2016.

Cited by: 3|Bibtex|Views26
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Other Links: dblp.uni-trier.de|academic.microsoft.com

Abstract:

Methods for action recognition have evolved considerably over the past years and can now automatically learn and recognize short term actions with satisfactory accuracy. Nonetheless, the recognition of complex activities - compositions of actions and scene objects - is still an open problem due to the complex temporal and composite struct...More

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