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Advances in Photometric 3D-Reconstruction / edited by Jean-Denis Durou, Maurizio Falcone, Yvain Quéau, Silvia Tozza

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Advances in Computer Vision and Pattern Recognition | Springer eBook CollectionPublisher: Cham : Springer International Publishing, 2020Publisher: Cham : Imprint: Springer, 2020Edition: 1st ed. 2020Description: 1 Online-Ressource(VII, 234 p. 112 illus., 64 illus. in color.)ISBN:
  • 9783030518660
Subject(s): Additional physical formats: 9783030518653 | 9783030518677 | 9783030518684 | Erscheint auch als: 9783030518653 Druck-Ausgabe | Erscheint auch als: 9783030518677 Druck-Ausgabe | Erscheint auch als: 9783030518684 Druck-AusgabeDOI: DOI: 10.1007/978-3-030-51866-0Online resources: Summary: 1. A Comprehensive Introduction to Photometric 3D-Reconstruction -- 2. Perspective Shape from Shading an Exposition on Recent Works with New Experiments -- 3. RGBD-Fusion: Depth Refinement for Diffuse and Specular Objects -- 4. Non-Rigid Structure from Motion and Shading -- 5. On the Well-Posedness of Uncalibrated Photometric Stereo Under General Lighting.Summary: This book presents the latest advances in photometric 3D reconstruction. It provides the reader with an overview of the state of the art in the field, and of the latest research into both the theoretical foundations of photometric 3D reconstruction and its practical application in several fields (including security, medicine, cultural heritage and archiving, and engineering). These techniques play a crucial role within such emerging technologies as 3D printing, since they permit the direct conversion of an image into a solid object. The book covers both theoretical analysis and real-world applications, highlighting the importance of deepening interdisciplinary skills, and as such will be of interest to both academic researchers and practitioners from the computer vision and mathematical 3D modeling communities, as well as engineers involved in 3D printing. No prior background is required beyond a general knowledge of classical computer vision models, numerical methods for optimization, and partial differential equations. .PPN: PPN: 1734625880Package identifier: Produktsigel: ZDB-2-SCS | ZDB-2-SEB | ZDB-2-SXCS
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