Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
Saliency, Scale and Image Description
International Journal of Computer Vision
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
A representation for visual information with application to machine vision
A representation for visual information with application to machine vision
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Comparison of Affine Region Detectors
International Journal of Computer Vision
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
A sparse curvature-based detector of affine invariant blobs
Computer Vision and Image Understanding
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In this paper we present a novel scale invariant interest point detector of blobs which incorporates the idea of blob movement along the scales. This trajectory of the blobs through the scale space is shown to be valuable information in order to estimate the most stable locations and scales of the interest points. Our detector evaluates interest points in terms of their self trajectory along the scales and its evolution obtaining non-redundant and discriminant features. Moreover, in this paper we present a differential geometry view to understand how interest points can be detected. We propose to analyze the gaussian curvature to classify image regions as blobs, edges or corners. Our interest point detector has been compared with some of the most important scale invariant detectors on infrared (IR) images, outperforming their results in terms of: number of interest points detected and discrimination of the interest points.