Using a Reference Point for Local Configuration of SIFT-like Features
Language
English
Type
Proceedings of Japanese Conferences
Authors
Martin Klinkigt, Koichi Kise
Title
Using a Reference Point for Local Configuration of SIFT-like Features
Journal
Proc. of Meeting on Image Recognition and Understanding (MIRU)
Presentation number
IS2-29
Pages
pp.960-967
Reviewed
Not reviewed
Date
July 2010
Research fields
Object Recognition
Key
Klinkigt2010_MIRU (id=1185)
Abstract
In this paper we propose a model to describe the local configuration of SIFT-like features. This information helps to overcome the problem with background clutter in images, i.e., information extracted from areas in the image, which do not belong to the object. Our model is not static as many other proposed models. Instead we calculate during detection a reference point of the object and verify this with the features extracted from the query image. This additional step increases the detection performance around 6\% even under hard conditions, for example, if training images and query images contain background clutter.
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