Applied Graph Theory in Computer Vision and Pattern Recognition

Applied Graph Theory in Computer Vision and Pattern Recognition

Author: Abraham Kandel

Publisher: Springer Science & Business Media

Published: 2007-03-12

Total Pages: 265

ISBN-13: 3540680195

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This book presents novel graph-theoretic methods for complex computer vision and pattern recognition tasks. It presents the application of graph theory to low-level processing of digital images, presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, and provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks.


Graph-Based Representations in Pattern Recognition

Graph-Based Representations in Pattern Recognition

Author: Pasquale Foggia

Publisher: Springer

Published: 2017-05-08

Total Pages: 290

ISBN-13: 331958961X

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This book constitutes the refereed proceedings of the 11th IAPR-TC-15 International Workshop on Graph-Based Representation in Pattern Recognition, GbRPR 2017, held in Anacapri, Italy, in May 2017. The 25 full papers and 2 abstracts of invited papers presented in this volume were carefully reviewed and selected from 31 submissions. The papers discuss research results and applications in the intersection of pattern recognition, image analysis, graph theory, and also the application of graphs to pattern recognition problems in other fields like computational topology, graphic recognition systems and bioinformatics.


Graph-Based Methods in Computer Vision: Developments and Applications

Graph-Based Methods in Computer Vision: Developments and Applications

Author: Bai, Xiao

Publisher: IGI Global

Published: 2012-07-31

Total Pages: 395

ISBN-13: 1466618922

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Computer vision, the science and technology of machines that see, has been a rapidly developing research area since the mid-1970s. It focuses on the understanding of digital input images in many forms, including video and 3-D range data. Graph-Based Methods in Computer Vision: Developments and Applications presents a sampling of the research issues related to applying graph-based methods in computer vision. These methods have been under-utilized in the past, but use must now be increased because of their ability to naturally and effectively represent image models and data. This publication explores current activity and future applications of this fascinating and ground-breaking topic.


Graph-Based Representations in Pattern Recognition

Graph-Based Representations in Pattern Recognition

Author: Donatello Conte

Publisher: Springer

Published: 2019-06-10

Total Pages: 257

ISBN-13: 3030200817

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This book constitutes the refereed proceedings of the 12th IAPR-TC-15 International Workshop on Graph-Based Representation in Pattern Recognition, GbRPR 2019, held in Tours, France, in June 2019. The 22 full papers included in this volume together with an invited talk were carefully reviewed and selected from 28 submissions. The papers discuss research results and applications at the intersection of pattern recognition, image analysis, and graph theory. They cover topics such as graph edit distance, graph matching, machine learning for graph problems, network and graph embedding, spectral graph problems, and parallel algorithms for graph problems.


Graph-Based Representations in Pattern Recognition

Graph-Based Representations in Pattern Recognition

Author: Xiaoyi Jiang

Publisher: Springer

Published: 2011-05-05

Total Pages: 355

ISBN-13: 3642208444

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This book constitutes the refereed proceedings of the 8th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, 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.


Graph-based Representations in Pattern Recognition

Graph-based Representations in Pattern Recognition

Author: Donatello Conte

Publisher:

Published: 2019

Total Pages: 247

ISBN-13: 9783030200824

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This book constitutes the refereed proceedings of the 12th IAPR-TC-15 International Workshop on Graph-Based Representation in Pattern Recognition, GbRPR 2019, held in Tours, France, in June 2019. The 22 full papers included in this volume together with an invited talk were carefully reviewed and selected from 28 submissions. The papers discuss research results and applications at the intersection of pattern recognition, image analysis, and graph theory. They cover topics such as graph edit distance, graph matching, machine learning for graph problems, network and graph embedding, spectral graph problems, and parallel algorithms for graph problems.


Graph-Based Representations in Pattern Recognition

Graph-Based Representations in Pattern Recognition

Author: Andrea Torsello

Publisher: Springer Science & Business Media

Published: 2009-07-09

Total Pages: 387

ISBN-13: 3642021247

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This book constitutes the refereed proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2009, held in Venice, Italy in May 2009. The 37 revised full papers presented were carefully reviewed and selected from 47 submissions. The papers are organized in topical sections on graph-based representation and recognition, graph matching, graph clustering and classification, pyramids, combinatorial maps, and homologies, as well as graph-based segmentation.


Graph-Based Representations in Pattern Recognition

Graph-Based Representations in Pattern Recognition

Author: Luc Brun

Publisher: Springer

Published: 2005-03-10

Total Pages: 395

ISBN-13: 3540319883

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Many vision problems have to deal with di?erent entities (regions, lines, line junctions, etc.) and their relationships. These entities together with their re- tionships may be encoded using graphs or hypergraphs. The structural inf- mation encoded by graphs allows computer vision algorithms to address both the features of the di?erent entities and the structural or topological relati- ships between them. Moreover, turning a computer vision problem into a graph problem allows one to access the full arsenal of graph algorithms developed in computer science. The Technical Committee (TC15, http://www.iapr.org/tcs.html) of the IAPR (International Association for Pattern Recognition) has been funded in order to federate and to encourage research work in these ?elds. Among its - tivities, TC15 encourages the organization of special graph sessions at many computer vision conferences and organizes the biennial workshop GbR. While being designed within a speci?c framework, the graph algorithms developed for computer vision and pattern recognition tasks often share constraints and goals with those developed in other research ?elds such as data mining, robotics and discrete geometry. The TC15 community is thus not closed in its research ?elds but on the contrary is open to interchanges with other groups/communities.


Graph-Based Representations in Pattern Recognition

Graph-Based Representations in Pattern Recognition

Author: Cheng-Lin Liu

Publisher: Springer

Published: 2015-05-04

Total Pages: 382

ISBN-13: 3319182242

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This book constitutes the refereed proceedings of the 10th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, 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.


Graph-Based Representations in Pattern Recognition

Graph-Based Representations in Pattern Recognition

Author: Mario Vento

Publisher: Springer Nature

Published: 2023-08-23

Total Pages: 193

ISBN-13: 3031427955

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This book constitutes the refereed proceedings of the 13th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2023, which took place in Vietri sul Mare, Italy, in September 2023. The 16 full papers included in this book were carefully reviewed and selected from 18 submissions. They were organized in topical sections on graph kernels and graph algorithms; graph neural networks; and graph-based representations and applications.