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View-based 3-D object retrieval /

Content-based 3-D object retrieval has attracted extensive attention recently and has applications in a variety of fields, such as, computer-aided design, tele-medicine, mobile multimedia, virtual reality, and entertainment. The development of efficient and effective content-based 3-D object retriev...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Gao, Yue (Autor), Dai, Qionghai (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam : Elsevier, [2014]
©2015
Colección:Computer science reviews and trends.
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Gao, Yue,  |e author. 
245 1 0 |a View-based 3-D object retrieval /  |c Yue Gao, Qionghai Dai. 
260 |a Amsterdam :  |b Elsevier,  |c [2014] 
264 4 |c ©2015 
300 |a 1 online resource (154 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file 
490 1 |a Computer science reviews and trends 
504 |a Includes bibliographical references. 
520 |a Content-based 3-D object retrieval has attracted extensive attention recently and has applications in a variety of fields, such as, computer-aided design, tele-medicine, mobile multimedia, virtual reality, and entertainment. The development of efficient and effective content-based 3-D object retrieval techniques has enabled the use of fast 3-D reconstruction and model design. Recent technical progress, such as the development of camera technologies, has made it possible to capture the views of 3-D objects. As a result, view-based 3-D object retrieval has become an essential but challenging research topic. View-based 3-D Object Retrieval introduces and discusses the fundamental challenges in view-based 3-D object retrieval, proposes a collection of selected state-of-the-art methods for accomplishing this task developed by the authors, and summarizes recent achievements in view-based 3-D object retrieval. Part I presents an Introduction to View-based 3-D Object Retrieval, Part II discusses View Extraction, Selection, and Representation, Part III provides a deep dive into View-Based 3-D Object Comparison, and Part IV looks at future research and developments including Big Data application and geographical location-based applications. Systematically introduces view-based 3-D object retrieval, including problem definitions and settings, methodologies, and benchmark testing beds Discusses several key challenges in view-based 3-D object retrieval, and introduces the state-of-the-art solutions Presents the progression from general image retrieval techniques to view-based 3-D object retrieval Introduces future research efforts in the areas of Big Data, feature extraction, and geographical location-based applications. 
505 0 |a Front Cover; View-Based 3-D Object Retrieval; Copyright; Contents; Acknowledgments; Preface; Part I: The Start; Chapter 1: Introduction; 1.1 The Definition of 3DOR; 1.2 Model-Based 3DOR Versus View-Based 3DOR; 1.3 The Challenges of V3DOR; 1.4 Summary of Our Work; 1.4.1 View Extraction; 1.4.2 Representative View Selection; 1.4.3 Learning the Weights for Multiple Views; 1.4.4 Distance Measures for Object Matching; 1.4.5 Learning the Relevance Among 3-D Objects; 1.5 Structure of This Book; 1.6 Summary; References; Chapter 2: The Benchmark and Evaluation; 2.1 Introduction 
505 8 |a 2.2 The Standard Benchmarks2.3 The Shape Retrieval Contest; 2.4 Evaluation Criteria in 3DOR; 2.5 Summary; References; Part II View Extraction, Selection, and Representation; Chapter 3: View Extraction; 3.1 Introduction; 3.2 Dense Sampling Viewpoints; 3.3 Predefined Camera Array; 3.4 Generated View; 3.5 Summary; References; Chapter 4: View Selection; 4.1 Introduction; 4.2 Unsupervised View Selection; 4.3 Interactive View Selection; 4.3.1 Multiview 3-D Object Matching; 4.3.2 View Clustering; 4.3.3 Initial Query View Selection; 4.3.4 Interactive View Selection with User Relevance Feedback 
505 8 |a 4.3.5 Learning a Distance Metric4.3.6 Multiple Query Views Linear Combination; 4.3.7 The Computational Cost; 4.4 Summary; References; Chapter 5: View Representation; 5.1 Introduction; 5.2 Shape Feature Extraction; 5.2.1 Zernike Moments; 5.2.2 Fourier Descriptor; 5.3 The Bag-of-Visual-Features Method; 5.3.1 The Bag-of-Visual-Words; 5.3.2 The Bag-of-Region-Words; 5.4 Learning the Weights for Multiple Views; 5.4.1 K-Partite Graph Reinforcement; 5.4.2 Weight Learning for Multiple Views Usingthe k-Partite Graph; 5.5 Summary; References; Part III View-Based 3-D Object Comparison 
505 8 |a Chapter 6: Multiple-View Distance Metric6.1 Introduction; 6.2 Fundamental Many-to-Many Distance Measures; 6.3 Bipartite Graph Matching; 6.3.1 View Selection and Weighting; 6.3.2 Bipartite Graph Construction; 6.3.3 Bipartite Graph Matching; 6.4 Statistical Matching; 6.4.1 Adaptive View Clustering; 6.4.2 CCFV; 6.4.2.1 View Clustering and Query Model Training; 6.4.2.2 Positive and Negative Matching Models; 6.4.2.3 Calculation of the Similarity Between Q and O S(Q, O); 6.4.2.4 Analysis of Computational Cost; 6.4.3 Markov Chain; 6.4.4 Gaussian Mixture Model Formulation 
505 8 |a 6.4.4.1 Conventional GMM Training6.4.4.2 Generative Adaptation of GMM; 6.4.4.3 Discriminative Adaptation of GMM; 6.4.4.4 Learning the Weights for Multiple GMMs; 6.5 Summary; References; Chapter 7: Learning-Based 3-D Object Retrieval; 7.1 Introduction; 7.2 Learning Optimal Distance Metrics; 7.2.1 Hausdorff Distance Learning; 7.2.2 Learning Bipartite Graph Optimal Matching; 7.3 3-D Object Relevance Estimation via Hypergraph Learning; 7.3.1 Hypergraph and Its Applications; 7.3.2 Learning on Single Hypergraph; 7.3.3 Learning on Multiple Hypergraphs 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
650 0 |a Image processing. 
650 0 |a Pattern recognition systems. 
650 6 |a Traitement d'images. 
650 6 |a Reconnaissance des formes (Informatique) 
650 7 |a image processing.  |2 aat 
650 7 |a TECHNOLOGY & ENGINEERING  |x Mechanical.  |2 bisacsh 
650 7 |a Image processing  |2 fast 
650 7 |a Pattern recognition systems  |2 fast 
700 1 |a Dai, Qionghai,  |e author. 
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830 0 |a Computer science reviews and trends. 
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