| Description |
1 online resource (275 pages) |
| Contents |
3.4.2 Selection of Essential Keypoints (for Word Spotting) -- 3.4.3 Spotting Zones -- 3.4.4 Ranking of Spotted Zone -- 4 Experimental Results -- 4.1 Datasets and Ground Truth for Word Spotting -- 4.2 Datasets and Ground Truth for Figure Spotting -- 4.3 Determining the Value of -- 4.4 Selecting the Value of k -- 4.5 Results and Analysis -- 5 Conclusion -- References -- Part II Restoration and Reconstruction of Digital Heritage Artifacts -- Text Extraction and Restoration of Old Handwritten Documents -- 1 Introduction -- 1.1 Dataset -- 2 Literature Review -- 3 Proposed Method |
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Intro -- Preface -- Acknowledgments -- Organization -- Contents -- Part I Classification and Retrieval of Heritage Data -- Introduction to Heritages and Heritage Management: A Preview -- 1 Introduction -- 2 Classification of Heritages -- 3 Mapping of World Heritages -- 4 Digital Heritage -- 5 Public, Classified, and Personal Digital Heritage -- 6 Science and Digital Heritages -- 7 Computer-Based Processing of Digital Heritage -- 8 Threats to Digital Heritage -- 9 Motivation for Digital Heritage -- References -- Language-Based Text Categorization: A Survey -- 1 Introduction |
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1.1 Monolingual Text Categorization -- 1.2 Multilingual Text Classification -- 1.2.1 Automatic Language Identification -- 1.2.2 Preprocessing -- 1.2.3 Feature Extraction -- 1.2.4 Learning/Training Phase -- 1.3 Language and Document Models -- 1.4 Applications of Language Identification -- 1.5 Supervised Learning Methods for Text Categorization -- 1.5.1 Naïve Bayes Method -- 1.5.2 K-Nearest Neighbor -- 1.5.3 Support Vector Machine -- 1.5.4 Decision Tree Classifier -- 1.5.5 Neural Networks -- 1.5.6 Performance Measures -- 2 Related Work -- 2.1 Categorization of Monolingual Text Documents |
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2.2 Multilingual Text Categorization -- 2.3 Way Forward -- 3 Conclusion -- References -- Classification of Yoga Asanas from a Single Image by Learning the 3D View of Human Poses -- 1 Introduction -- 2 Related Work -- 2.1 Multiple-View 3D Human Pose Estimation -- 2.2 Single-View 3D Human Pose Estimation -- 3 Proposed Method -- 3.1 3D Pose Estimation -- 3.2 Classification of Yoga Asanas Based on Poses -- 4 Dataset and Experiments -- 5 Results -- 6 Observations/Conclusion -- References -- IHIRD: A Data Set for Indian Heritage Image Retrieval -- 1 Introduction -- 2 Description of the Data Set |
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3 Data Set Preparation -- 4 Development of Content-Based Image Retrieval System -- 4.1 Selection of Feature Descriptor and Distance Function -- 4.2 Indexing of the Image Database -- 4.3 Ontology-Driven Content-Based Image Search -- 5 Experimental Results -- 6 Conclusion -- References -- Object Spotting in Historical Documents -- 1 Introduction -- 2 Related Work -- 2.1 Word Spotting -- 2.2 Figure Spotting -- 3 Proposed Method -- 3.1 Keypoint Detection -- 3.2 Keypoint Descriptor -- 3.3 Estimation of Laplace-Beltrami Operator -- 3.4 Object Spotting -- 3.4.1 Candidate Keypoint Selection |
| Summary |
This book describes various new computer based approaches which can be exploited for the (digital) reconstruction, recognition, restoration, presentation and classification of digital heritage. They are based on applications of virtual reality, augmented reality and artificial intelligence, to be used for storing and retrieving of historical artifacts, digital reconstruction, or virtual viewing |
| Notes |
3.1 Training Data Generation |
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Print version record |
| Subject |
Historic preservation -- Technological innovations
|
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Cultural property -- Protection -- Technological innovations
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| Genre/Form |
Electronic books
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| Form |
Electronic book
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| Author |
Mukhopadhyay, Jayanta (College teacher)
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Sreedevi, Indu
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Chanda, B. (Bhabatosh)
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Chaudhury, Santanu.
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Namboodiri, Vinay P
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| ISBN |
9783030579074 |
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3030579077 |
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