Using Head Movement to Recognize Activity

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Venue:
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Year:
2000

Citing 0
Cited 2

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Abstract

This paper presents a methodology for automatically identifying human actions in either the frontal or the lateral view. By tracking the movement of the head of the subject over successive frames of a monocular grayscale image sequence, we recognize 12 different actions. The head is segmented automatically in each frame, and the feature vectors extracted. Input sequences captured from a fixed CCD camera are matched against stored models of actions. The system uses the nearest neighbor classifier to identify the test action.