Tracking human motion using multiple cameras

Presents a framework for tracking human motion in an indoor environment from sequences of monocular grayscale images obtained from multiple fixed cameras. Multivariate Gaussian models are applied to find the most likely matches of human subjects between consecutive frames taken by cameras mounted in...

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Bibliographic Details
Published inProceedings of 13th International Conference on Pattern Recognition Vol. 3; pp. 68 - 72 vol.3
Main Authors Cai, Q., Aggarwal, J.K.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1996
Subjects
Cameras
Computer vision
Contracts
Gray-scale
Humans
Indoor environments
Monitoring
Robustness
Shape
Tracking
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Summary:Presents a framework for tracking human motion in an indoor environment from sequences of monocular grayscale images obtained from multiple fixed cameras. Multivariate Gaussian models are applied to find the most likely matches of human subjects between consecutive frames taken by cameras mounted in various locations. Experimental results from real data show the robustness of the algorithm and its potential for real time applications.
ISBN:9780818672828
081867282X
ISSN:1051-4651
DOI:10.1109/ICPR.1996.546796