Detectability, uniqueness, and reliability of eigen windows forstable verification of partially occluded objects
Ohba, K.
Ikeuchi, K.
Mech. Eng. Lab., Minist. of Int. Trade & Ind., Tsukuba;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Sep 1997
Volume: 19,
Issue: 9
On page(s): 1043-1047
ISSN: 0162-8828
References Cited: 5
CODEN: ITPIDJ
INSPEC Accession Number: 5727082
Digital Object Identifier: 10.1109/34.615453
Current Version Published: 2002-08-06
Abstract
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
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
