Understanding visual behaviour

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Understanding visual behaviour
Modelling events is one of the key problems in dynamic scene analysis when salient and autonomous visual changes occuring in a scene need to be characterised effectively as meaningful events. We propose a new approach for modelling such temporal events based on the local intensity temporal history of pixels. The method provides a computationally very effective temporal measure for detecting autonomous events. Events are represented and detected first at the pixel level and then at a blob level (grouped pixels) autonomously. The Expectation-Maximisation (EM) algorithm is employed to cluster events with automatic model order selection using modified Minimum Description Length (MDL). Experiments are presented to demonstrate that meaningful clusters of blob-level events can be formed without object segmentation and tracking.
Shaogang Gong, Hilary Buxton
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 2002
Where IVC
Authors Shaogang Gong, Hilary Buxton
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