View-based 3-D Object Retrieval

個数:1
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  • ポイントキャンペーン

View-based 3-D Object Retrieval

  • 著者名:Gao, Yue/Dai, Qionghai
  • 価格 ¥6,315 (本体¥5,741)
  • Morgan Kaufmann(2014/12/04発売)
  • 春分の日の三連休!Kinoppy 電子書籍・電子洋書 全点ポイント30倍キャンペーン(~3/22)
  • ポイント 1,710pt (実際に付与されるポイントはご注文内容確認画面でご確認下さい)
  • 言語:ENG
  • ISBN:9780128024195
  • eISBN:9780128026236

ファイル: /

Description

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

Table of Contents

Part I The Start1. Introduction2. The Benchmark and EvaluationPart II View Extraction, Selection, and Representation3. View Extraction4. View Selection5. View RepresentationPart III View-Based 3-D Object Comparison6. Multiple-View Distance Metric7. Learning-based 3-D Object RetrievalPart IV Conclusion8. Conclusions and Future Work

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