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- Reiss, Attila, et al.
(author)
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Activity Recognition Using Biomechanical Model Based Pose Estimation
- 2010
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In: Smart Sensing and Context, 2010. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642169816 - 9783642169823 ; , s. 42-55
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Conference paper (peer-reviewed)abstract
- In this paper, a novel activity recognition method based on signal-oriented and model-based features is presented. The model-based features are calculated from shoulder and elbow joint angles and torso orientation, provided by upper-body pose estimation based on a biomechanical body model. The recognition performance of signal-oriented and model-based features is compared within this paper, and the potential of improving recognition accuracy by combining the two approaches is proved: the accuracy increased by 4–6% for certain activities when adding model-based features to the signal-oriented classifier. The presented activity recognition techniques are used for recognizing 9 everyday and fitness activities, and thus can be applied for e.g., fitness applications or ‘in vivo’ monitoring of patients.
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