Functional templates and their application to 3-D object recognition

A new approach to shape matching and knowledge-based signal processing, called functional template correlation (FTC), is presented in the context of 3D object recognition. Incorporating aspects of fuzzy set theory, functional templates (FTs) define, for each template point, arbitrarily complex tolerances of input image values. With this approach, object- and sensor-dependent knowledge is easily encoded in FTs, making it possible to effectively deal with uncertain or variable object appearance noise occlusion, and articulation. The output of FTC is a map of match scores, reflecting pixel-by-pixel belief of whether or not an encoded shape is present. Such maps can be combined using simple rules of arithmetic and are used to guide selective attention. The use of FTC is illustrated with examples from work in automatic recognition