Abstract
A unified framework is developed for efficiently solving a wide range of computational vision problems by performing adaptive scale space tracking (where a solution at a coarse resolution is tracked to solutions at ever increasing resolution). This approach is motivated by physical smoothness models, deformable sheets, based on thin elastic membranes and plates. The inherent smoothness properties of the deformable sheets act against externally applied, problem specific forces derived from images. The authors also developed the necessary relations for quantitative control of scale based parameters so that the scale space tracking process can be completely automated. Finally, they present solutions to different problems in computational vision using the framework applied to real images. >
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