NDLI: Representing object manifolds by parametrized SOMs

Content Provider	IEEE Xplore Digital Library
Author	Saalbach, A. Heidemann, G. Ritter, H.
Copyright Year	2002
Description	Author affiliation: Fac. of Technol., Bielefeld Univ., Germany (Saalbach, A.; Heidemann, G.; Ritter, H.)
Abstract	The recognition and pose estimation of three-dimensional objects is a challenging task that requires suitable object representations. In this paper, we propose the "parametrized self-organizing map" (PSOM) as a flexible method for the generation of appearance-based object models. A PSOM in an eigenspace can be used to extend multiple views of an object to a continuous parametrized manifold that describes the object appearance under various conditions. In a computer vision application the distance from an unknown input to the object specific PSOMs can be used for classification, and the projection on the manifold gives additional informations about additional scene parameters like object pose or illumination direction. We illustrate this concept in a benchmark example that is based on the COIL-20 database which consists of 20 different objects in 72 poses.
Starting Page	184
Ending Page	187
File Size	258805
Page Count	4
File Format	PDF
ISBN	076951695X
ISSN	10514651
DOI	10.1109/ICPR.2002.1048268
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-08-11
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Nearest neighbor searches Sampling methods Interpolation Layout Computer vision Solid modeling Humans Machine learning Neural networks Manifolds
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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