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Classification of Upper Limb Motion Trajectories Using Shape Features

Zhou, H and Hu, H and Liu, H and Tang, J (2012) 'Classification of Upper Limb Motion Trajectories Using Shape Features.' IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 42 (6). pp. 970-982. ISSN 1094-6977

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Abstract

To understand and interpret human motion is a very active research area nowadays because of its importance in sports sciences, health care, and video surveillance. However, classification of human motion patterns is still a challenging topic because of the variations in kinetics and kinematics of human movements. In this paper, we present a novel algorithm for automatic classification of motion trajectories of human upper limbs. The proposed scheme starts from transforming 3-D positions and rotations of the shoulder/elbow/wrist joints into 2-D trajectories. Discriminative features of these 2-D trajectories are, then, extracted using a probabilistic shape-context method. Afterward, these features are classified using a k-means clustering algorithm. Experimental results demonstrate the superiority of the proposed method over the state-of-the-art techniques.

Item Type: Article
Uncontrolled Keywords: Classification; expectation maximization; health care; motion trajectory; shape contexts (SCs)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 06 Mar 2013 11:41
Last Modified: 15 Jan 2022 00:41
URI: http://repository.essex.ac.uk/id/eprint/5519

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