Using head movement to recognize activity

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 automa...

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Bibliographic Details
Main Authors: Madabhushi, A., Aggarwal, J.K.
Format: Conference Proceeding
Language:English
Subjects:
Charge coupled devices
Charge-coupled image sensors
Feature extraction
Gray-scale
Head
Humans
Image recognition
Image segmentation
Image sequences
Tracking
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Summary: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.
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2000.903013