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Geometric min-Hashing: Finding a (Thick) Needle in a Haystack
(IEEE, 2009-06)
We propose a novel hashing scheme for image retrieval, clustering and automatic object discovery. Unlike commonly used bag-of-words approaches, the spatial extent of image features is exploited in our method. The geometric ...
Efficient Representation of Local Geometry for Large Scale Object Retrieval
(IEEE, 2009-06)
State of the art methods for image and object retrieval exploit both appearance (via visual words) and local geometry (spatial extent, relative pose). In large scale problems, memory becomes a limiting factor - local ...
Construction of Precise Local Affine Frames
(IEEE, 2010-08)
We propose a novel method for the refinement of Maximally Stable Extremal Region (MSER) boundaries to sub-pixel precision by taking into account the intensity function in the 2 × 2 neighborhood of the contour points. The ...
Image Matching and Retrieval by Repetitive Patterns
(IEEE, 2010-08)
Detection of repetitive patterns in images has been studied for a long time in computer vision. This paper discusses a method for representing a lattice or line pattern by shift-invariant descriptor of the repeating element. ...
Epipolar Geometry from Two Correspondences
(IEEE, 2006)
A novel algorithm for robust RANSAC-like estimation of epipolar geometry (of uncalibrated camera pair) from two correspondences of local affine frames (LAFs) is presented. Each LAF is constructed from three points independently ...