Context-Based Segmentation of Image Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model Selection for Unsupervised Learning of Visual Context
International Journal of Computer Vision
ANGELAH: a framework for assisting elders at home
IEEE Journal on Selected Areas in Communications - Special issue on wireless and pervasive communications for healthcare
Learning semantic scene models by trajectory analysis
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
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MAP estimation of Gaussian mixtures through maximisation of penalised likelihoods was used to learn models of spatial context. This enabled prior beliefs about the scale, orientation and elongation of semantic regions to be encoded, encouraging one-to-one correspondences between mixture components and these regions. In conjunction with minimum description length this enabled automatic learning of inactivity zones and entry zones from track data in a supportive home environment.