Invariance against local affine deformation for feature based object detection systems

In this paper, we present a method to increase invariance against affine deformations in feature based object detection systems. We use the gradient distribution of an image region to calculate two non-orthogonal basis vectors defining an affine invariant coordinate system, which is used to normaliz...

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Bibliographic Details
Published in2016 Picture Coding Symposium (PCS) pp. 1 - 5
Main Authors Bulla, Christopher, Ohm, Jens-Rainer
Format Conference Proceeding
LanguageEnglish
Published IEEE 2016
Subjects
Computational complexity
Covariance matrices
Detectors
Distortion
Feature extraction
Mathematical model
Matrix decomposition
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Summary:In this paper, we present a method to increase invariance against affine deformations in feature based object detection systems. We use the gradient distribution of an image region to calculate two non-orthogonal basis vectors defining an affine invariant coordinate system, which is used to normalize the image region. The proposed method is an intermediate processing step subsequent to the feature detection and can be combined with any feature detector and descriptor combination. Its performance is evaluated on locally affine transformed as well as on real world images and compared to state of the art methods for affine invariant feature description. The observed results outperform the results obtained by SIFT, ASIFT or the Harris-Affine based feature normalization method, without introducing significant additional demands on the memory requirement or the computational complexity.
ISSN:2472-7822
DOI:10.1109/PCS.2016.7906351