This is a course that has been succesfuly offered at the Graduate Center since Fall of 2003. It covers a topic of great research and commercial interest, i.e. the acquisition and processing of 3D models of real environments. There is a large volume of research work and industrial commintment on that field. A great number of our recent PhD graduates concentrate on that topic.
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 recent papers. The research facilities of the Vision and Graphics Laboratory will become available to registered class participants. The research of our laboratory has been supported by the National Science Foundation So, if you are interested for a research topic, please join the class!
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.
3D laser sensing and 2D image sensing.
Classification in 3D point clouds
About the instructor
Ioannis Stamos is working in the areas of Computer Vision and Computer Graphics. His current research interests are in the broad area of photorealistic 3-D model acquisition and the utilization of dense range 3-D data. He has been working on range image segmentation, 3-D modeling and range to image registration algorithms. He received his Ph.D. from the Computer Science Department of Columbia University on 2001, his M.S. and M.Phil. from the same department and his Diploma of Engineering from the University of Patras (Department of Computer Engineering), Greece. Ioannis Stamos is a recipient of the Faculty Early Career Development Award (CAREER) by the National Science Foundation. He is currently supported by a number of NSF awards.