Results 11  20
of
360
Efficient Identification of Web Communities
 IN SIXTH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING
, 2000
"... We define a community on the web as a set of sites that have more links (in either direction) to members of the community than to nonmembers. Members of such a community can be eciently identified in a maximum flow / minimum cut framework, where the source is composed of known members, and the sink ..."
Abstract

Cited by 293 (13 self)
 Add to MetaCart
We define a community on the web as a set of sites that have more links (in either direction) to members of the community than to nonmembers. Members of such a community can be eciently identified in a maximum flow / minimum cut framework, where the source is composed of known members, and the sink consists of wellknown nonmembers. A focused crawler that crawls to a fixed depth can approximate community membership by augmenting the graph induced by the crawl with links to a virtual sink node. The effectiveness of the approximation algorithm is demonstrated with several crawl results that identify hubs, authorities, web rings, and other link topologies that are useful but not easily categorized. Applications of our approach include focused crawlers and search engines, automatic population of portal categories, and improved filtering.
Computing geodesics and minimal surfaces via graph cuts
 in International Conference on Computer Vision
, 2003
"... Geodesic active contours and graph cuts are two standard image segmentation techniques. We introduce a new segmentation method combining some of their benefits. Our main intuition is that any cut on a graph embedded in some continuous space can be interpreted as a contour (in 2D) or a surface (in 3D ..."
Abstract

Cited by 251 (26 self)
 Add to MetaCart
(Show Context)
Geodesic active contours and graph cuts are two standard image segmentation techniques. We introduce a new segmentation method combining some of their benefits. Our main intuition is that any cut on a graph embedded in some continuous space can be interpreted as a contour (in 2D) or a surface (in 3D). We show how to build a grid graph and set its edge weights so that the cost of cuts is arbitrarily close to the length (area) of the corresponding contours (surfaces) for any anisotropic Riemannian metric. There are two interesting consequences of this technical result. First, graph cut algorithms can be used to find globally minimum geodesic contours (minimal surfaces in 3D) under arbitrary Riemannian metric for a given set of boundary conditions. Second, we show how to minimize metrication artifacts in existing graphcut based methods in vision. Theoretically speaking, our work provides an interesting link between several branches of mathematicsdifferential geometry, integral geometry, and combinatorial optimization. The main technical problem is solved using CauchyCrofton formula from integral geometry. 1.
Motion Segmentation and Tracking Using Normalized Cuts
, 1998
"... We propose a motion segmentation algorithm that aims to break a scene into its most prominent moving groups. A weighted graph is constructed on the ira. age sequence by connecting pixels that arc in the spatiotemporal neighborhood of each other. At each pizel, we define motion profile vectors which ..."
Abstract

Cited by 179 (6 self)
 Add to MetaCart
(Show Context)
We propose a motion segmentation algorithm that aims to break a scene into its most prominent moving groups. A weighted graph is constructed on the ira. age sequence by connecting pixels that arc in the spatiotemporal neighborhood of each other. At each pizel, we define motion profile vectors which capture the probability distribution of the image veloczty. The distance between motion profiles is used to assign a weight on the graph edges. 5rsmg normalized cuts we find the most salient partitions of the spatiotemporaI graph formed by the image sequence. For swmenting long image sequences,' we have developed a recursire update procedure that incorporates knowledge of segmentation in previous frames for efficiently finding the group correspondence in the new frame.
A Clustering Algorithm based on Graph Connectivity
 Information Processing Letters
, 1999
"... We have developed a novel algorithm for cluster analysis that is based on graph theoretic techniques. ..."
Abstract

Cited by 138 (3 self)
 Add to MetaCart
(Show Context)
We have developed a novel algorithm for cluster analysis that is based on graph theoretic techniques.
Fast Multiscale Image Segmentation
"... We introduce a fast, multiscale algorithm for image segmentation. Our algorithm uses modern numeric techniques to nd an approximate solution to normalized cut measures in time that is linear in the size of the image with only a few dozen operations per pixel. In just one pass the algorithm provides ..."
Abstract

Cited by 136 (13 self)
 Add to MetaCart
(Show Context)
We introduce a fast, multiscale algorithm for image segmentation. Our algorithm uses modern numeric techniques to nd an approximate solution to normalized cut measures in time that is linear in the size of the image with only a few dozen operations per pixel. In just one pass the algorithm provides a complete hierarchical decomposition of the image into segments. The algorithm detects the segments by applying a process of recursive coarsening in which the same minimization problem is represented with fewer and fewer variables producing an irregular pyramid. During this coarsening process we may compute additional internal statistics of the emerging segments and use these statistics to facilitate the segmentation process. Once the pyramid is completed it is scanned from the top down to associate pixels close to the boundaries of segments with the appropriate segment. The algorithm is inspired by algebraic multigrid (AMG) solvers of minimization problems of heat or electric networks. We demonstrate the algorithm by applying it to real images.
Flexible Syntactic Matching of Curves and its Application to Automatic Hierarchical Classification of Silhouettes
 IEEE Transactions on Pattern Analysis and Machine Intelligence
"... Curve matching is one instance of the fundamental correspondence problem. Our exible algorithm is designed to match curves under substantial deformations and arbitrary large scaling and rigid transformations. A syntactic representation is constructed for both curves, and an edit transformation which ..."
Abstract

Cited by 131 (2 self)
 Add to MetaCart
(Show Context)
Curve matching is one instance of the fundamental correspondence problem. Our exible algorithm is designed to match curves under substantial deformations and arbitrary large scaling and rigid transformations. A syntactic representation is constructed for both curves, and an edit transformation which maps one curve to the other is found using dynamic programming. We present extensive...
Statistical Region Merging
 IEEE Trans. on Pattern Analysis and Machine Intelligence
, 2004
"... This paper explores a statistical basis for a process often described in computer vision: image segmentation by region merging following a particular order in the choice of regions. We exhibit a particular blend of algorithmics and statistics whose segmentation error is, as we show, limited from b ..."
Abstract

Cited by 129 (9 self)
 Add to MetaCart
(Show Context)
This paper explores a statistical basis for a process often described in computer vision: image segmentation by region merging following a particular order in the choice of regions. We exhibit a particular blend of algorithmics and statistics whose segmentation error is, as we show, limited from both the qualitative and quantitative standpoints. This approach can be efficiently approximated in linear time/space, leading to a fast segmentation algorithm tailored to processing images described using most common numerical pixel attribute spaces. The conceptual simplicity of the approach makes it simple to modify and cope with hard noise corruption, handle occlusion, authorize the control of the segmentation scale, and process unconventional data such as spherical images. Experiments on graylevel and color images, obtained with a short readily available Ccode, display the quality of the segmentations obtained.
Constrained Parametric MinCuts for Automatic Object Segmentation
, 2010
"... We present a novel framework for generating and rankingplausibleobjectshypothesesin animage using bottomup processes and midlevel cues. The object hypotheses arerepresented as figureground segmentations, and are extracted automatically, withoutpriorknowledgeabout properties of individual object c ..."
Abstract

Cited by 123 (11 self)
 Add to MetaCart
(Show Context)
We present a novel framework for generating and rankingplausibleobjectshypothesesin animage using bottomup processes and midlevel cues. The object hypotheses arerepresented as figureground segmentations, and are extracted automatically, withoutpriorknowledgeabout properties of individual object classes, by solving a sequence of constrained parametric mincut problems (CPMC) on a regular image grid. We then learn to rank the object hypotheses by training a continuous model to predict how plausible the segments are, given their midlevel region properties. We show that this algorithm significantly outperforms the state of the art for lowlevel segmentation in the VOC09 segmentation dataset. It achieves the same average best segmentation covering as the best performing technique to date [2], 0.61 when using just the top 7 ranked segments, instead of the full hierarchy in [2]. Our methodachieves0.78averagebest covering using 154 segments. In a companion paper [18], we also show that the algorithm achieves stateofthe art results when used in a segmentationbased recognition pipeline.
Interactive Graph Cut Based Segmentation With Shape Priors
 IN CVPR, PAGES I: 755–762
, 2005
"... ... alternative to pure automatic segmentation in many applications. While automatic segmentation can be very challenging, a small amount of user input can often resolve ambiguous decisions on the part of the algorithm. In this work, we devise a graph cut algorithm for interactive segmentation which ..."
Abstract

Cited by 116 (0 self)
 Add to MetaCart
... alternative to pure automatic segmentation in many applications. While automatic segmentation can be very challenging, a small amount of user input can often resolve ambiguous decisions on the part of the algorithm. In this work, we devise a graph cut algorithm for interactive segmentation which incorporates shape priors. While traditional graph cut approaches to interactive segmentation are often quite successful, they may fail in cases where there are diffuse edges, or multiple similar objects in close proximity to one another. Incorporation of shape priors within this framework mitigates these problems. Positive results on both medical and natural images are demonstrated.
Image Segmentation Using Local Variation
 in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
, 1998
"... We present a new graphtheoretic approach to the problem of image segmentation. Our method uses local criteria and yet produces results that reflect global properties of the image. We develop a framework that provides specific definitions of what it means for an image to be under or oversegmented. ..."
Abstract

Cited by 114 (3 self)
 Add to MetaCart
(Show Context)
We present a new graphtheoretic approach to the problem of image segmentation. Our method uses local criteria and yet produces results that reflect global properties of the image. We develop a framework that provides specific definitions of what it means for an image to be under or oversegmented. We then present an efficient algorithm for computing a segmentation that is neither under nor oversegmented according to these definitions. Our segmentation criterion is based on intensity differences between neighboring pixels. An important characteristic of the approach is that it is able to preserve detail in lowvariability regions while ignoring detail in highvariability regions, which we illustrate with several examples on both real and sythetic images.