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2008

Image Feature Localization by Multiple Hypothesis Testing of Gabor Features

8 years 11 months ago
Image Feature Localization by Multiple Hypothesis Testing of Gabor Features
Several novel and particularly successful object and object category detection and recognition methods based on image features, local descriptions of object appearance, have recently been proposed. The methods are based on a localization of image features and a spatial constellation search over the localized features. The accuracy and reliability of the methods depend on the success of both tasks: image feature localization and spatial constellation model search. In this paper, we present an improved algorithm for image feature localization. The method is based on complex-valued multiresolution Gabor features and their ranking using multiple hypothesis testing. The algorithm provides very accurate local image features over arbitrary scale and rotation. We discuss in detail issues such as selection of filter parameters, confidence measure, and the magnitude versus complex representation, and show on a large test sample how these influence the performance. The versatility and accuracy of...
Jarmo Ilonen, Joni-Kristian Kamarainen, Pekka Paal
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where TIP
Authors Jarmo Ilonen, Joni-Kristian Kamarainen, Pekka Paalanen, Miroslav Hamouz, Josef Kittler, Heikki Kälviäinen
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