Video Modelling and Segmentation Using Gaussian Mixture Models

Authors:
Xiaoran Mo;Roland Wilson
Affiliations:
University of Warwick, Coventry, UK;University of Warwick, Coventry, UK
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Year:
2004

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Abstract

This paper describes a new approach to the video modelling and segmentation problem using Gaussian mixture model descriptors. These have several advantages over conventional, histogram-based techniques, including: a rigorous statistical basis; the possibility of encoding spatial, colour, texture and motion features in a unified system; and the ability to trade off accuracy of representation against data volume. After a brief introduction to the class of models, results are presented to show their efficacy.