The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.09 - September (1997 vol.19)
pp: 1043-1048
ABSTRACT
<p><b>Abstract</b>—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, <it>detectability</it>, <it>uniqueness</it>, and <it>reliability</it>, 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.</p>
INDEX TERMS
Object recognition, multiple objects, eigenspace, detectability, uniqueness, reliability.
CITATION
Kohtaro Ohba, Katsushi Ikeuchi, "Detectability, Uniqueness, and Reliability of Eigen Windows for Stable Verification of Partially Occluded Objects", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.19, no. 9, pp. 1043-1048, September 1997, doi:10.1109/34.615453
23 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool