This paper describes a technique for building compact models of the shape and appearance of flexible objects (such as organs) seen in 2D images. The models are derived from the statistics of labelled images containing examples of the objects. Each model consists of a flexible shape template, describing how the relevant locations of important points on the objects can vary, and a statistical model of the expected grey levels in a region around each model point. We describe how the models can be used in local image search, and give examples of their application to medical images.
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