1st Edition
Handbook of 3D Machine Vision Optical Metrology and Imaging
Stereo Vision
Soon-Yong Park and Seung-Hae Baek
3D Shapes from Speckle
Yuan Hao Huang, Yang Shang, Yusheng Liu, and Hujun Bao
Spacetime Stereo
Li Zhang, Noah Snavely, Brian Curless, and Steven M. Seitz
Stereo Particle Imaging Velocimetry Techniques: Technical Basis, System Setup, and Application
Hui Hu
Basic Concepts
Sergio Fernandez and Joaquim Salvi
Digital Holography for 3D Metrology
Anand Asundi, Qu Weijuan, Chee Oi Choo, Kapil Dev, and Yan Hao
3D Dynamic Shape Measurement Using the Grating Projection Technique
Xianyu Su, Qican Zhang, and Wenjing Chen
Interferometry
David P. Towers and Catherine E. Towers
Superfast 3D Profilometry with Digital Fringe Projection and Phase-Shifting Techniques
Laura Ekstrand, Yajun Wang, Nikolaus Karpinsky, and Song Zhang
Time-of-Flight Techniques
Shoji Kawahito
Uniaxial 3D Shape Measurement
Yukitoshi Otani
Three-Dimensional Ultrasound Imaging
Aaron Fenster, Grace Parraga, Bernard Chiu, and Jeff Bax
Optical Coherence Tomography for Imaging Biological Tissue
Michael K.K. Leung and Beau A. Standish
Three-Dimensional Endoscopic Surface Imaging Techniques
Jason Geng
Biometrics Using 3D Vision Techniques
Maria De Marsico, Michele Nappi, and Daniel Riccio
Index
Biography
Dr. Song Zhang is an assistant professor of mechanical engineering at Iowa State University. His research interests include the fundamental physics of optical metrology, new mathematical and computational tools for 3D shape analysis, and designing superfast 3D imaging and sensing techniques. A recipient of the NSF CAREER award in 2012, Dr. Zhang has published over 40 peer-reviewed journal articles and authored four book chapters. He is a reviewer for over 20 international journals, a committee member for numerous conferences, and a cochair for several conferences.
"The chapters are well written and offer a uniform high standard of content. … This book should appeal to any academic or industrial researcher, or developer looking to expand their skills into machine vision: it would be particularly useful to any young researcher just starting out. The expert in the field should also find something of interest. The concepts outlined have wider applicability and this is a good place to start for anyone looking for an overview of these technologies."
—John Watson, University of Aberdeen, Optics and Lasers in Engineering
