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Detectability, uniqueness, and reliability of eigen windows for stable verification of partially occluded objects

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2 Author(s)
Ohba, K. ; Mech. Eng. Lab., Minist. of Int. Trade & Ind., Tsukuba, Japan ; Ikeuchi, K.

This paper describes a method for recognizing partially occluded objects for bin-picking tasks using eigenspace analysis, referred to as the “eigen window” method, that stores multiple partial appearances of an object in an eigenspace. Such partial appearances require a large amount of memory space. Three measurements, detectability, uniqueness, and reliability, on windows are developed to eliminate redundant windows and thereby reduce memory requirements. Using a pose clustering technique, the method determines the pose of an object and the object type itself. We have implemented the method and verified its validity

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:19 ,  Issue: 9 )