Graduate Center Image
Fall 2019, CSc 84060 :  3D Photography, Graduate Center of CUNY, Prof. Ioannis Stamos, Thursday 9:30am - 11:30am, Rm. TBD
istamos@hunter.cuny.edu
Office hours: 12 - 2 Tuesdays (1090K Hunter North), or after class.
Tentative schedule

Online
            detection

                                                                                                                                                  
Figure: (a) 3D range scan of Park Avenue and 70th street (scanner is a the center of the intersection). Bird's-eye view. Data gathered by the Leica ScanStation2 of our laboratory. (b) 3D texture-mapped model of building at CCNY. Camera positions are shown (see IJCV 2008 paper in publications). (c) Online classification of objects in urban scene (red is vegetation)
       


Course Overview

Recent advances in computer hardware have made possible the efficient rendering of realistic 3D models in inexpensive PCs, something that was possible with high end visualization workstations only a few years ago. This class will cover the field of 3D Photography -the process of automatically creating 3D texture mapped models of objects- in detail. 
We will concentrate on the topics at the intersection of Computer Vision and Computer Graphics that are relevant to acquiring, creating, and representing 3D models of small objects or large urban areas. Many very interesting research questions need to be answered. For example: how do we acquire real shapes? how do we represent geometry? can we detect similarities between shapes? can we detect symmetries within shapes? how do we register 3D geometry with color images?, etc. Applications that benefit by this technology include:  historical preservation, urban planning, google-type maps, architecture, navigation, virtual reality, e-commerce, digital cinematography, computer games,  just to name a few.

The core of the class will be a set of presentations of research papers. 

Course Format

There will be a weekly class, with presentations by the instructor. The presentations will introduce the basic concepts and techniques of the field.
Each student will present one or two assigned topics in class. Outstanding projects can lead to successful PhD theses, and to research paper submissions.

The grade will be based upon the following: 
50% for group or individual projects, 30% for presentation(s) and 20% for class participation.




Prerequisites
Students need to be familiar with at least one of the following topics: Image/Pixel Processing, Computer Vision, Computer Graphics, or Robotics. A prerequisite can be waived by permission of the instructor. Please contact Prof. Stamos directly if you feel you do not have the required qualifications.




Topics



References

This class will be based on recent publications and recent workshops. A set of seminars, books, and journals are provided for your reference.

Computer Vision Books:

Computer Vision: Algorithms and Applications, Richard Szeliski, 2010: Online Version
Introductory Techniques for 3-D Computer Vision. EmanueleTrucco and Alessandro Verri. Prentice Hall, 1998.
Robot Vision. B. K. P. Horn, The MIT Press, 1998 (12th printing).
Three-Dimensional Computer Vision: A Geometric Viewpoint. Olivier Faugeras, The MIT Press, 1996.
An Invitation to 3-D Vision. Yi Ma, Stefano Soatto, Jana Kosecka, S. Shankar Sastry. Springer-Verlag, 2004.
Computer Vision A Modern approach.  David S. Forsyth, Jean Ponce. Prentice Hall 2003.
Computer Vision. Linda Shapiro and George Stockman. Prentice Hall, 2001.

Computer Graphics Books:

Computer Graphics, Principles and Practice. Foley, van Dam, Feiner, and Hudges. Addison-Wesley, 1997.
3D Computer Graphics. Alan Watt. Addison-Wesley, 2000.
OpenGL Programming Guide. Mason Woo, Jackie Neider, Tom Davis. Addison-Wesley, 1998.

Computer Vision and Graphics Journals:

International Journal on Computer Vision
.
Computer Vision and Image Understanding
.
IEEE Trans. on Pattern Analysis and Machine Intelligence
.
SIGGRAPH (http://www.siggraph.org).