Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Matching Widely Separated Views Based on Affine Invariant Regions
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
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In this paper, we aim to address the problem of automatic scale selection for image features like corners and junctions. Image neighborhood of these features usually contain the background and multiple foreground surfaces, thus can not be correctly described by a single scale. We show that the proposed Fan Laplacian-of-Gaussian (FLOG) kernel is capable to select the appropriate scales for independent image partitions that can represent meaningful physical surfaces attached to the corner or junction. Support for the proposed method is given in terms of theoretical investigation and experiments on real images.