16-823: Physics based Methods in Vision, Spring 2019

General Information

Time:  Tuesdays and Thursdays, 1:30 pm  -- 2:50 pm

Location: NSH 3002

Pre-requisites: Any undergraduate or graduate Vision, Graphics, or Image processing or equivalent course 

Announcements

Instructor 

Matthew O'Toole 

Instructor's website: http://www.cs.cmu.edu/~motoole2

Email: mpotoole@cmu.edu

Office: Smith Hall 215

Office Hours: By appointment (refer to Google calendar for available time slots)

Overview

Everyday, we observe an extraordinary array of light and color phenomena around us, ranging from the dazzling effects of the atmosphere, the complex appearances of surfaces and materials, and underwater scenarios. For a long time, artists, scientists, and photographers have been fascinated by these effects, and have focused their attention on capturing and understanding these phenomena. In this course, we take a computational approach to modeling and analyzing these phenomena, which we collectively call "visual appearance". The first half of the course focuses on the physical fundamentals of visual appearance, while the second half of the course focuses on algorithms and applications in a variety of fields such as computer vision, graphics and remote sensing and technologies such as underwater and aerial imaging. This course unifies concepts usually learnt in physical sciences and their application in imaging sciences. Students attending this course will learn about the fundamental building blocks that describe visual appearance, and recent academic papers on a variety of physics-based methods that measure, process, and analyze visual information from the real world.

List of Topics


Optional  Texts

Grading

Lecture Presentations

[Acknowledgements]

A significant part of this course is similar to the courses offered at Stanford (Pat Hanrahan, Marc Levoy, Ron Fediw), UC San Diego (Henrik Wann Jensen), Columbia (Shree Nayar, Peter Belhumeur, Ravi Ramamoorthi), UW Madison (Chuck Dyer), UWash (Steve Seitz), Utah (Pete Shirley), Rutgers (Kristin Dana), Cornell (Steve Marschner, Kavita Bala), Technion (Yoav Schechner), Princeton (Szymon Rusinkiewicz), MIT (Ted Adelson), Drexel (Ko Nishino), TU Berlin and Deutsch Telecom (Rahul Swaminathan). These slides were largely put together in previous offerings of the course by Srinivasa Narasimhan. The instructor thanks the instructors of these courses for the materials (slides, content) used in this course. In addition, several photographs and illustrations are borrowed from internet sources. The instructor thanks them all.

[Permission to use/modify materials]

The instructor gladly gives permission to use and modify any of the slides for academic and research purposes. Since a lot of the material is borrowed from other sources, please acknowledge the original sources too. Finally, since this is a continuously evolving course, all suggestions and corrections (major, minor) are welcome!