Graduate Center Image
Fall CSc 83020:  3D Computer Vision, Graduate Center of CUNY, Prof. Ioannis Stamos, Wednesday 9:30-11:30AM, Rm. 3305
Office hours: Tuesdays 4:00-6:00 (at Hunter) or by appointment
Tentative schedule for Fall 2012


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 (see 3DPVT 2010 paper).

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:  image retrieval in digital libraries, image search, face recognition, 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 recent papers along with introduction of fundamental topics. The research facilities of the Vision and Graphics Laboratory will become available to registered class participants. The research of our laboratory is supported by the National Science Foundation through three active NSF awards. So, if you are interested for a research topic, please join the class!

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.

The grade will be based upon the following: 
60% for group/individual projects, 30% for final project and 10% for class participation.


Linear algebra, data structures and algorithms, and C/C++ or Java programming. No prior knowledge of vision is assumed. Courses such as image processing, computer graphics, and digital tomography are helpful but are not required for the understanding of the material.


Course Material

Tentative schedule for Fall 2012


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).
Computer Vision A Modern approach.  David S. Forsyth, Jean Ponce. Prentice Hall 2003. Some online content.
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. 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