View-Based 3-D Object Retrieval

Author:   Yue Gao ,  Qionghai Dai
Publisher:   Elsevier Science
ISBN:  

9780128026236


Publication Date:   01 January 2014
Format:   Electronic book text
Availability:   Available To Order   Availability explained
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View-Based 3-D Object Retrieval


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Overview

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 bedsDiscusses several key challenges in view-based 3-D object retrieval, and introduces the state-of-the-art solutionsPresents the progression from general image retrieval techniques to view-based 3-D object retrievalIntroduces future research efforts in the areas of Big Data, feature extraction, and geographical location-based applications

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Author:   Yue Gao ,  Qionghai Dai
Publisher:   Elsevier Science
Imprint:   Elsevier Science
ISBN:  

9780128026236


ISBN 10:   0128026235
Publication Date:   01 January 2014
Audience:   General/trade ,  General
Format:   Electronic book text
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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