Advances in Photometric 3d-Reconstruction

ISBN-13: 9783030518653 / Angielski / Twarda / 2020 / 234 str.

Jean-Denis Durou; Maurizio Falcone; Yvain Quéau

Spis treści

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.- 6. Recent Progress in Shape from Polarization.- 7. Estimating Facial Aging using Light Scattering Photometry.

O autorze

Dr. Jean-Denis Durou is an Associate Professor at the University of Toulouse (IRIT, CNRS), France.

Dr. Maurizio Falcone is a Professor of Numerical Analysis in the Department of Mathematics at Sapienza University of Rome, Italy.

Dr. Yvain Quéau is a CNRS Researcher in the GREYC Laboratory at the University of Caen Normandy, France.

Dr. Silvia Tozza is a Research Assistant at the “Renato Caccioppoli” Department of Mathematics and Applications, University of Naples Federico II, Italy.   

Blurb

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.