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Object Recognition using Multiple Cues

We here present a system based on multiple cues for object recognition containing a new method for color contour selection using color prototype modeled by fuzzy sets. In addition an object representation is presented that enables predictions for an active vision system. The design of the system is motivated by two evaluations that is also presented here. The extraction of color contours is motivated by an evaluation of a local shape descriptor, shape context, and a local photometric descriptors, SIFT, performance in object recognition on two different data sets. The use of fuzzy color membership functions enables selection of contours by backprojecting the membership function and detecting edges in the membership map. The utility of this approach is tested by its use in contour recognition, using shape context, in cluttered environments.