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Digital techniques for heritage pres...

Mukhopadhyay, Jayanta.

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Digital techniques for heritage presentation and preservation

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Digital techniques for heritage presentation and preservation/ edited by Jayanta Mukhopadhyay ... [et al.].
其他作者:	Mukhopadhyay, Jayanta.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	xiv, 272 p. :ill., digital ;24 cm.
內容註:	Part I: Classification and Retrieval of Heritage Data -- Introduction to Heritages and HeritageManagement: A Preview -- Language-Based Text Categorization: A Survey -- Classification of Yoga Asanas from a Single Image by Learning the 3D View of Human Poses -- IHIRD: A Data Set for Indian Heritage Image Retrieval -- Object Spotting in Historical Documents -- Part II: Restoration and Reconstruction of Digital Heritage Artifacts -- Text Extraction and Restoration of Old Handwritten Documents -- Categorization and Selection of Crowdsourced Images Towards 3D Reconstruction of Heritage Sites -- Deep Learning-Based Filtering of Images for 3D Reconstruction of Heritage Sites -- Improving Landmark Recognition Using Saliency Detection and Feature Classification -- Part III: Applications ofModern Tools in Digital Heritage -- Bharatanatyam Dance Transcription Using Multimedia Ontology and Machine Learning -- Evolution and Interconnection: Geometry in Early Temple Architecture -- Computer Vision for Capturing Flora.
Contained By:	Springer Nature eBook
標題:	Historic preservation - Technological innovations. -
電子資源:	https://doi.org/10.1007/978-3-030-57907-4
ISBN:	9783030579074

Digital techniques for heritage presentation and preservation
Digital techniques for heritage presentation and preservation[electronic resource] /edited by Jayanta Mukhopadhyay ... [et al.]. - Cham :Springer International Publishing :2021. - xiv, 272 p. :ill., digital ;24 cm.

Part I: Classification and Retrieval of Heritage Data -- Introduction to Heritages and HeritageManagement: A Preview -- Language-Based Text Categorization: A Survey -- Classification of Yoga Asanas from a Single Image by Learning the 3D View of Human Poses -- IHIRD: A Data Set for Indian Heritage Image Retrieval -- Object Spotting in Historical Documents -- Part II: Restoration and Reconstruction of Digital Heritage Artifacts -- Text Extraction and Restoration of Old Handwritten Documents -- Categorization and Selection of Crowdsourced Images Towards 3D Reconstruction of Heritage Sites -- Deep Learning-Based Filtering of Images for 3D Reconstruction of Heritage Sites -- Improving Landmark Recognition Using Saliency Detection and Feature Classification -- Part III: Applications ofModern Tools in Digital Heritage -- Bharatanatyam Dance Transcription Using Multimedia Ontology and Machine Learning -- Evolution and Interconnection: Geometry in Early Temple Architecture -- Computer Vision for Capturing Flora.

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. The book is divided into three sections: "Classification of Heritage Data" presents chapters covering various domains and aspects including text categorization, image retrieval and classification, and object spotting in historical documents. Next, in "Detection and Recognition of Digital Heritage Artifacts", techniques like neural networks or deep learning are used for the restoration of degraded heritage documents, Tamil Palm Leaf Characters recognition, the reconstruction of heritage images, and the selection of suitable images for 3D reconstruction and classification of Indian land mark heritage images. Lastly, "Applications of Modern Tools in Digital Heritage" highlights some example applications for dance transcription, architectural geometry of early temples by digital reconstruction, and computer vision based techniques for collecting and integrating knowledge on flora. This book is mainly written for researchers and graduate students in digital preservation and heritage, or computer scientists looking for applications of virtual reality, computer vision, and artificial intelligence techniques.

ISBN: 9783030579074

Standard No.: 10.1007/978-3-030-57907-4doiSubjects--Topical Terms:

1622185
Historic preservation
--Technological innovations.

LC Class. No.: CC135 / .D54 2021

Dewey Class. No.: 004

Digital techniques for heritage presentation and preservation
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505 0 $a Part I: Classification and Retrieval of Heritage Data -- Introduction to Heritages and HeritageManagement: A Preview -- Language-Based Text Categorization: A Survey -- Classification of Yoga Asanas from a Single Image by Learning the 3D View of Human Poses -- IHIRD: A Data Set for Indian Heritage Image Retrieval -- Object Spotting in Historical Documents -- Part II: Restoration and Reconstruction of Digital Heritage Artifacts -- Text Extraction and Restoration of Old Handwritten Documents -- Categorization and Selection of Crowdsourced Images Towards 3D Reconstruction of Heritage Sites -- Deep Learning-Based Filtering of Images for 3D Reconstruction of Heritage Sites -- Improving Landmark Recognition Using Saliency Detection and Feature Classification -- Part III: Applications ofModern Tools in Digital Heritage -- Bharatanatyam Dance Transcription Using Multimedia Ontology and Machine Learning -- Evolution and Interconnection: Geometry in Early Temple Architecture -- Computer Vision for Capturing Flora.
520 $a 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. The book is divided into three sections: "Classification of Heritage Data" presents chapters covering various domains and aspects including text categorization, image retrieval and classification, and object spotting in historical documents. Next, in "Detection and Recognition of Digital Heritage Artifacts", techniques like neural networks or deep learning are used for the restoration of degraded heritage documents, Tamil Palm Leaf Characters recognition, the reconstruction of heritage images, and the selection of suitable images for 3D reconstruction and classification of Indian land mark heritage images. Lastly, "Applications of Modern Tools in Digital Heritage" highlights some example applications for dance transcription, architectural geometry of early temples by digital reconstruction, and computer vision based techniques for collecting and integrating knowledge on flora. This book is mainly written for researchers and graduate students in digital preservation and heritage, or computer scientists looking for applications of virtual reality, computer vision, and artificial intelligence techniques.
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