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Object Localization Based on Markov Random Fields and Symmetry Interest Points
  • Object Localization Based on Markov Random Fields and Symmetry Interest Points
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ai.stanford.edu
We present an approach to detect anatomical structures by configurations of interest points, from a single example image. The representation of the configuration is based on Markov Random Fields, and the detection is performed in a single iteration by the max-sum algorithm....
Rene Donner, Branislav Micusík, Georg Langs, Lech Szumilas, Philipp Peloschek, Klaus Friedrich, Horst Bischof
MICCAI - 2007
Springer
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Scale-invariant medial features based on gradient vector flow fields
  • Scale-invariant medial features based on gradient vector flow fields
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www.kyb.mpg.de
We propose a novel set of medial feature interest points based on gradient vector flow (GVF) fields [18]. We exploit the long ranging GVF fields for symmetry estimation by calculating the flux flow on it. We propose interest points that are located on maxima of that flux flow and offer a straight forward way to estimate salient local scales....
ICPR - 2008
IEEE
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Vector Field Convolution for Image Segmentation using Snakes
  • Vector Field Convolution for Image Segmentation using Snakes
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viva.ee.virginia.edu
Snakes, or active contours, have been widely used in image processing applications. Typical roadblocks to consistent performance include limited capture range, noise sensitivity, and poor convergence to concavities. This paper proposes a new design for the snake external force, called vector field convolution (VFC), to address these problems....
Bing Li, Scott T. Acton
ICIP - 2006
IEEE
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Detecting Rotational Symmetries
  • Detecting Rotational Symmetries
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www.umiacs.umd.edu
We present an algorithm for detecting multiple rotational symmetries in natural images. Given an image, its gradient magnitude field is computed, and information from the gradients is spread using a diffusion process in the form of a Gradient Vector Flow (GVF) field....
V. Shiv Naga Prasad, Larry S. Davis
ICCV - 2005
IEEE
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Robust Centerline Extraction Framework Using Level Sets
  • Robust Centerline Extraction Framework Using Level Sets
mecca.louisville.edu
In this paper, we present a novel framework for computing centerlines for both 2D and 3D shape analysis. The framework works as follows: an object centerline point is selected automatically as the point of global maximum Euclidean distance from the boundary, and is considered a point source (PS) that transmits a wave front that evolves over time and traverses the object domain....
M. Sabry Hassouna
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Robust Centerline Extraction Framework Using Level Sets
  • Robust Centerline Extraction Framework Using Level Sets
mecca.louisville.edu
In this paper, we present a novel framework for computing centerlines for both 2D and 3D shape analysis. The framework works as follows: an object centerline point is selected automatically as the point of global maximum Euclidean distance from the boundary, and is considered a point source (PS) that transmits a wave front that evolves over time and traverses the object domain....
M. Sabry Hassouna, Aly A. Farag
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On the Extraction of Curve Skeletons using Gradient Vector Flow
  • On the Extraction of Curve Skeletons using Gradient Vector Flow
mecca.louisville.edu
In this paper, we propose a new variational framework for computing continuous curve skeletons from discrete objects that are suitable for structural shape representation. We have derived a new energy function, which is proportional to some medialness function, such that the minimum cost path between any two medial voxels in the shape is a curve skeleton....
M. Sabry Hassouna, Aly A. Farag
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Variational Curve Skeletons Using Gradient Vector Flow
  • Variational Curve Skeletons Using Gradient Vector Flow
mecca.louisville.edu
Representing a 3D shape by a set of one-dimensional curves that are locally symmetric with respect to its boundary (i.e., curve skeletons) is of importance in several machine intelligence tasks. This paper presents a fast, automatic, and robust variational framework for computing continuous, sub-voxel accurate curve skeletons from volumetric objects....
M. Sabry Hassouna, Aly A. Farag