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Comparing grid-based features and classification settings, in an off-line supervised human action detection and recognition task

Hijmans, Remco (2012) Comparing grid-based features and classification settings, in an off-line supervised human action detection and recognition task.

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Abstract:This master thesis describes a final project, where two different grid-based features using different classification settings are compared, in an off-line supervised human action detection and recognition task. The task consists of the detecting and recognizing �tness moves performed in an exercise video, using limited training data acquired from the same video.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Human Media Interaction MSc (60030)
Link to this item:http://purl.utwente.nl/essays/61708
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