CMU-CS-96-105
Computer Science Department
School of Computer Science, Carnegie Mellon University


CMU-CS-96-105

Recognition of the Multi Specularity Objects using the Eigen-Window

Kohtaro Ohba, Katsushi Ikeuchi

February 1996

[Also appears as CMU-]

CMU-CS-96-100.ps


Keywords: Object recognition, specularity, multi objects, Eigen-space


29 pages

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@center(FTP: CMU-CS-95-105.ps.gz) This paper describes a method for recognizing partially occluded objects for bin-picking tasks using the eigen-space analysis. Although effective in recognizing an isolated object, as was shown by Murase and Nayar, the current method cannot be applied to partially occluded objects that are typical in bin-picking tasks. The analy sis also requires that the object is centered in an image before recognition. These limitations of the eigen-space analysis are due to the fact that the whole appearance of an object is utilized as a template for the analysis. We propose a new method, referred to as the "eigen-window" method, that stores multiple partial appearances of an object in an eigen-space. Such partial appearances require a large number of memory space. A similarity measure among windows is developed to eliminate redundant windows and thereby reduce memory requirement. Using a pose cluster ing method among windows, the method determines the pose of an object and the object type of itself. We have implemented the method and verify the validity of the method.