Computational Photography
(1051-753)
Spring, 2011
Time: Tu, 1:00pm-3:50pm
Room: COL(18)-1080
 |
 |
 |
 |
| Camera arrays and plenoptic cameras are used to
capture light fields for refocusing, 3D displays,
and many other applications. |
The Nokia N900, a Linux-based camera phone with a
5-megapixel camera, focusable lens, WiFi, and
touchscreen. |
Computational lighting has been widely used in movie industry
to capture live performance of actors and render in
virtual environment. |
Global illumination, such as the inter-reflection
between the eggs, can now be easily separated with
computational illumination.
|
Course Information
Professor: Jinwei
Gu
Email: jwgu@cis.rit.edu
Office: COL(18)-1081
Phone: 585-475-6783
Office Hours: Monday 3:50pm-4:50pm (or by appointment).
TA: TBA
Email: TBA@rit.edu
Office: TBA
Office Hour: TBA
Description
Computational photography is an emerging field that aims to
overcome the limitations of conventional digital imaging and
display devices by using computational techniques and
statistical priors to perform more efficient and accurate
measurement as well as produce more compelling and meaningful
visualizations of the world around us. It is a convergence of
many areas, such as computer vision, computer graphics, image
processing, photography, and so on.
In this course, we will study many interesting, recent
techniques for capturing, modeling, and displaying of complex
appearance phenomena. Students will implement some of these
techniques. We will cover topics such as computational sensors
with assorted pixel, mobile camera control, light field capture
and rendering, computational flash photography, computational
illumination for appearance acquisition and 3D reconstruction,
reflectance transformation imaging, light transport analysis,
novel displays and printing techniques.
The course will consist of four programming
homework, a presentation and paper review about one relevant
paper, and a student-chosen final project. There is no midterm
or final exam. We will provide a Nokia N900 cell phone
camera with open source SDK as a test-bed for this course.
Prerequisite
Basic knowledge of radiometry, image processing, and linear
algebra. Programming skills are Matlab or IDL, as well as some
basic C/C++ programming (skeleton code will be provided). If you
are not sure whether you can take the course, please send me
email or talk to me!
Topics
- Image Formation, Camera Model
- Computational Sensor, Assorted Pixel
- HDR Imaging
- Light Field Capture and Rendering
- Computational Camera
- Computational Flash Photography
- Photometric Stereo
- BRDF Acquisition
- Light Transport Analysis
- Image Relighting
- Light Multiplexing
- Novel Displays and Printing
- ...
Course Format
- Lectures: The instructor will give the lecture
each week, covering a background introduction of the topic
and the key points/skills for each topic.
- Paper Review and Presentation: Starting from
the 3rd week, one selected student will present a relevant
paper (usually a recent publication in the referred
conference/journal) in the second class of each week (about
30 minutes). Depending on the course enrollment, one or more
papers might be presented each class. The presenter
will also fill out a review form for the selected paper.
- Homework: There will be THREE programming homework.
- Final Project: Students can select a final
project (a list of possible project ideas will be provided
here).
Students are allowed to work on a project in groups of two.
During the quarter, they will need to submit a proposal, an
intermediate milestone report, a final project presentation,
and a final report.
Grading
- Homework (40%=3*13.3%)
- Paper Review/Presentation (15%=5%+10%, bouns point 10%
per extra paper, up to 2 papers)
- Final Project (40%=5%+10%+15%+10%)
- Class Attendance (5%)
Texts
Computational photography is a new, active research area. No
standard textbook is available. Handouts will be delivered
during class. Course content will keep updated. Lots of
resources are available online. See below for useful links.
Homework
- HW1: Camera Calibration/HDR Imaging/Tone Mapping
- HW2: FrankenCamera Control
- HW3: Photometric Stereo
- HW4: Separation of Direct and Global Illumination
Submissions
Dropboxes will be available on the myCourses website for
submission of homework and final project.
Tentative Schedule
Lecture Notes: Slides presented in class will be posted
in the content area of myCourses. The tentative
syllabus is subject to change (but not much) and update.
|
Date |
Title |
Topic |
Paper Presenter |
Readings/Demos |
Assignment |
| Week 1 |
March 8 |
Introduction |
Introduction, radiometry review |
|
|
Paper List Out Assign paper presentation |
| Week 2 |
March 15 |
Image Formation |
Camera, Lens, Image Formation |
|
|
Project List Out Ask for Project Proposal |
| Week 3 |
March 22 |
Light Field |
Plenoptic Function, Light Field |
* |
|
HW1 Out
Project Proposal Back |
| Week 4 |
March 29 |
Computational Sensor |
HDR Imaging, Assorted Pixel |
* |
|
|
| Week 5 |
April 5 |
Computational Camera |
FrankenCamera, Camera Controls |
* |
|
HW1 Back FrankenCamera Setup |
| Week 6 |
April 12 |
Computational Illumination (1) |
Multiplexing, Flash Photography |
* |
|
|
| Week 7 |
April 19 |
Computational Illumination (2) |
Photometric Stereo, BRDF Acquisition |
* |
|
Project Milestone Report Back HW2 Out |
| Week 8 |
April 26 |
Light Transport Analysis |
Direct/Global Illumination, Inter-reflection |
* |
|
|
| Week 9 |
May 3 |
Novel Displays |
Image Relighting, Light Sensitive Displays, Light
Field Displays |
* |
|
HW2 Back HW3 Out |
| Week 10 |
May 10 |
Printing Materials Final Project Presentation |
Printing BRDF, Subsurface Scattering |
|
|
|
| Week 11 |
May 17 |
Final Project Presentation |
|
|
|
Project Report Back HW3 Back |
Useful Links
(will keep updating)
Similar Courses in Other Universities:
- Computational
Photography SIGGRAPH Course (Raskar & Tumblin)
- Computational
Camera and Photography (Raskar, MIT)
- Digital
and Computational Photography (Durand & Freeman,
MIT)
- Computational Photography (Levoy & Wilburn,
Stanford)
- Computational
Photography (Belhumeur, Columbia)
- Computational
Photography (Efros, CMU)
- Computational
Photography (Essa, Georgia Tech)
- Computational
Photography (Fergus, NYU)
- Computer
Vision (Seitz, U of Washington)
- Computer
Vision (Zhang, U of Wisconsin)
- Computer
Vision (Snavely, Cornell)
- Introduction
to Visual Computing (Kutulakos, U of Toronto)
- Online book, Computer Vision:
Algorithms and Applications, by Richard
Szeliski.
More Links
- What
is Computational Camera, Shree Nayar, Columbia
-
Columbia Projects, Shree
Nayar, Peter Belhumeur
- MIT Projects, Fredo
Durand, William Freeman, Edward Adelson, Antonio
Torralba, Raskar
Ramesh
- Stanford Projects, Marc Levoy and collaborators
- USC Projects, Paul Debevec and
collaborators
- CMU Projects, Narasimhan, Efros
- Jack
Tumblin's 'Questions' for the field
- Richard Szeliski's
online Computer Vision Book
- Conferences: ICCP 2011,
ICCP
2010,
ICCP 2009,
SIGGRAPH, SIGGRAPH Asia, CVPR, ICCV, ECCV, ...
Acknowledgement
Many of the course materials are modified from the excellent
class notes of similar courses offered in other schools by Prof
Yung-Yu Chung, Frédo Durand,
Alexei Efros,
William Freeman, Shree Nayar Peter Belhumeur Marc Levoy Noah Snavely Li Zhang Srinivasa Narasimhan, Steve Seitz, and
Dr Richard
Szeliski. The instructor is extremely thankful to the
researchers for making their notes available online. Please feel free to
use and modify any of the slides but acknowledge the original sources
where appropriate.