In recent years graph embedding has emerged as a promising solution for enabling the expressive, convenient, powerful but computational expensive graphbasedrepresentations to benefit from mature, less expensive and ...
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graph centrality has been extensively applied in Social Network Analysis to model the interaction of actors and the information flow inside a graph. In this paper, we investigate the usage of graph centralities in the...
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A generic model-based segmentation algorithm is presented. based on a set of training data, consisting of images with corresponding object segmentations, a local appearance and local shape model is build. the object i...
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ISBN:
(纸本)9783642021237
A generic model-based segmentation algorithm is presented. based on a set of training data, consisting of images with corresponding object segmentations, a local appearance and local shape model is build. the object is described by a set of landmarks. For each landmark a local appearance model is build. this model describes the local intensity values in the image around each landmark. the local shape model is constructed by considering the landmarks to be vertices in an undirected graph. the edges represent the relations between neighboring landmarks. By implying the markovianity property on the graph, every landmark is only directly dependent upon its neighboring landmarks, leading to a local shape model. the objective function to be minimized is obtained from a maximum a-posteriori approach. To minimize this objective function, the problem is discretized by considering a finite set of possible candidates for each landmark. In this way the segmentation problem is turned into a labeling problem. Mean field annealing is used to optimize this labeling problem. the, algorithm is validated for the segmentation of teeth from cone beam computed tomography images and for automated cephalometric analysis.
the High Momentum Particle Identification Detector (HMPID), already installed in the ALICE setup at LHC, is ready to identify charged hadrons with momentum up to 5 GeV/c. It consists of seven modules of a RICH detecto...
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the High Momentum Particle Identification Detector (HMPID), already installed in the ALICE setup at LHC, is ready to identify charged hadrons with momentum up to 5 GeV/c. It consists of seven modules of a RICH detector with a CsI photocathode. the HMPID will operate to identify charged hadrons both in Pb-Pb collisions and in p-p collisions. the strategy to identify charged hadrons will differ according to the colliding system. In the case of central Pb-Pb collisions, the identification of Cherenkov photons requires efficient patternrecognition algorithm (based on a modified Hough transform, that maps the pad coordinate space directly to the Cherenkov angle parameter space). In the first p-p collisions, instead, where the tracking has to be optimized (or even missing, as sometimes in the cosmic runs), a first reconstruction step based on a new algorithm (Hidden Track Algorithm-HTA) will be used. the tracking parameters are not used in the patternrecognition, at the end an estimate of the track direction as well as the mean <theta(C)> will be performed. the HTA will be here described and preliminary results on its performances will be presented. (C) 2008 Elsevier B.V. All rights reserved.
this book constitutes the refereed proceedings of the 8th IAPR-TC-15 internationalworkshop on graph-basedrepresentations in patternrecognition, GbRPR 2011, held in Münster, Germany, in May 2011.;the 34 revised...
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ISBN:
(数字)9783642208447
ISBN:
(纸本)9783642208430
this book constitutes the refereed proceedings of the 8th IAPR-TC-15 internationalworkshop on graph-basedrepresentations in patternrecognition, GbRPR 2011, held in Münster, Germany, in May 2011.;the 34 revised full papers presented were carefully reviewed and selected from numerous submissions. the papers are organized in topical sections on graph-based representation and characterization, graph matching, classification, and querying, graph-based learning, graph-based segmentation, and applications.
Irregular pyramids are made of a stack of successively reduced graphs embedded in the plane. Such pyramids are often used within the segmentation and the connected component analysis frameworks to detect meaningful ob...
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ISBN:
(纸本)3540252703
Irregular pyramids are made of a stack of successively reduced graphs embedded in the plane. Such pyramids are often used within the segmentation and the connected component analysis frameworks to detect meaningful objects together withtheir spatial and topological relationships. the graphs reduced in the pyramid may be region adjacency graphs, dual graphs or combinatorial maps. Using any of these graphs each vertex of a reduced graph encodes a region of the image. Using simple graphs one edge between two vertices encodes the existence of a common boundary between two regions. Using dual graphs and combinatorial maps, each connected boundary segment between two regions is associated to one edge. Moreover, special edges called loops may be used to differentiate a special type of adjacency where one region surrounds the other. We show in this article that the loop information does not allow to distinguish inside and outside of the loop by local computations. We provide a method based on the combinatorial pyramid framework which uses the orientation explicitly encoded by combinatorial maps to determine inside and outside with local calculus.
the proceedings contain 127 papers. the special focus in this conference is on Visual recognition, Detection, Contours, Lines and Paths. the topics include: Finding clusters and components by unsupervised learning;a d...
ISBN:
(纸本)9783540225706
the proceedings contain 127 papers. the special focus in this conference is on Visual recognition, Detection, Contours, Lines and Paths. the topics include: Finding clusters and components by unsupervised learning;a demonstration on text data;the use of graph techniques for identifying objects and scenes in indoor building environments for mobile robots;graphical-based learning environments for patternrecognition;spectral analysis of complex laplacian matrices;a significant improvement of softassign with diffusion kernels;eigenspace method by autoassociative networks for object recognition;extraction of skeletal shape features using a visual attention operator;computing the cyclic edit distance for pattern classification by ranking edit paths;steady state random walks for path estimation;new variational framework for rigid-body alignment;an error-tolerant approximate matching algorithm for attributed planar graphs and its application to fingerprint classification;comparison of algorithms for web document clustering using graphrepresentations of data;a syntactic patternrecognition approach to computer assisted translation;a general methodology for finite-state translation using alignments;a comparison of unsupervised shot classification algorithms for news video segmentation;diagnosis of lung nodule using the semivariogram function;distances between distributions;multiscale curvature assessment of postural deviations;learning people movement model from multiple cameras for behaviour recognition;a comparison of least squares and spectral methods for attributed graph matching and an auction algorithm for graph-based contextual correspondence matching.
this book constitutes the refereed proceedings of the 6thinternationalworkshop on Structural and Syntactical patternrecognition, SSPR '96, held in Leipzig, Germany in August 1996.;the 36 revised full papers inc...
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ISBN:
(数字)9783540706311
ISBN:
(纸本)9783540615774
this book constitutes the refereed proceedings of the 6thinternationalworkshop on Structural and Syntactical patternrecognition, SSPR '96, held in Leipzig, Germany in August 1996.;the 36 revised full papers included together withthree invited papers were carefully selected from a total of 52 submissions. the papers are organized in topical sections on grammars and languages; morphology and mathematical approaches to patternrecognition; semantic nets, relational models and graph-based methods; 2D and 3D shape recognition; document image analysis and recognition; and handwritten and printed character recognition.
In this paper we describe modifications of irregular image segmentation pyramids based on user-interaction. We first build a hierarchy of segmentations by the minimum spanning tree based method, then regions from diff...
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ISBN:
(纸本)9783642208447
In this paper we describe modifications of irregular image segmentation pyramids based on user-interaction. We first build a hierarchy of segmentations by the minimum spanning tree based method, then regions from different (granularity) levels are combined to a final (better) segmentation with user-specified operations guiding the segmentation process. based on these operations the users can produce a final image segmentation that best suits their applications. this work can be used for applications where we need accuracy in image segmentation, in annotating images or creating ground truth among others.
this book constitutes the refereed proceedings of the 10th IAPR-TC-15 internationalworkshop on graph-basedrepresentations in patternrecognition, GbRPR 2015, held in Beijing, China, in May 2015. the 36 papers presen...
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ISBN:
(数字)9783319182247
ISBN:
(纸本)9783319182230
this book constitutes the refereed proceedings of the 10th IAPR-TC-15 internationalworkshop on graph-basedrepresentations in patternrecognition, GbRPR 2015, held in Beijing, China, in May 2015. the 36 papers presented in this volume were carefully reviewed and selected from 53 submissions. the accepted papers cover diverse issues of graph-based methods and applications, with 7 in graph representation,
15 in graph matching, 7 in graph clustering and classification, and 7 in graph-based applications.
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