Title :
Recognizing and locating partially occluded 2-D objects: symbolic clustering method
Author :
Wang, Vincent S S
Author_Institution :
Dept. of Comput. Sci., Texas Univ., Austin, TX, USA
Abstract :
Recognition of objects using a model can be formulated as the finding of affine transforms such that the locations of all object features are consistent with the projected position of the model from a single view. A method for the computing of the transform using the symbolic clustering method is described. The advantage of this approach is that the desired transform can be computed efficiently and in parallel. Experiments support this observation
Keywords :
pattern recognition; transforms; model; object location; partially occluded 2D objects; pattern recognition; symbolic clustering; transforms; Clustering methods; Computer architecture; Fuzzy logic; Image processing; Morphology; Nonlinear filters; Notice of Violation; Optical sensors; Signal processing algorithms; Statistics;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
