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Statistical shape-and-texture appearance models use image morphing to define a rich, compact representation of object appearance. They are useful in a variety of applications including object recognition, tracking and segmentation. These techniques, however, have been limited to objects with Lambertian surface reflectance, simple geometry and topology. In this work we present new shape-and-texture appearance models that overcome these limitations. In the first part of our work we develop a 4Ddoi:10.1016/j.cviu.2006.06.001 fatcat:tawp5wkgxjendmhkwfmv4hnmqe