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Supervised Segmentation and Tracking of Non-rigid Objects using a "Mixture of Histograms" Model

Mark Everingham, Barry Thomas, Supervised Segmentation and Tracking of Non-rigid Objects using a "Mixture of Histograms" Model. Proceedings of the 8th IEEE International Conference on Image Processing (ICIP 2001). -, (eds.), pp. 62–65. October 2001. PDF, 587 Kbytes.

Abstract

Segmentation and tracking of objects in video sequences is important for a number of applications. In the supervised variant, segmentation can be achieved by modelling the probability density of image observations taken from an object for use in a Bayesian classifier, and Gaussian mixture models have been applied to this task by several researchers. Motivated by practical difficulties we have experienced with these models we propose a novel and simple alternative approach which combines a strong shape model with histograms of image features and gives good empirical results on test sequences requiring flexible models.

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