CS410/510: Computational Photography

CS 410/510: Introduction to Computational Photography

Instructor: Feng Liu	TA: Zhan Li
Office: Zoom	Office: https://pdx.zoom.us/j/84063267395
Office Hours: email for an appointment	Office Hours: TR 14:30-15:30
Email: fliu@pdx.edu	Email: lizhan@pdx.edu

Announcements

In-class paper presentation schedule (sign in using your pdx email account)
You can use VPN to connect to the PSU network to download papers from IEEE or ACM.
This class will be taught remotely using the Zoom meeting system. The meeting link has been sent to your pdx.edu email account.

Computational photography is a field where computer graphics, computer vision, optics, and photography come together to create high-quality pictures. This course will discuss computational techniques to overcome the limitations of traditional cameras and enhance their capabilities. This course will cover topics ranging from concepts of digital camera and photography to computer vision and graphics techniques for creating high-quality pictures, including high dynamic range imaging, panorama stitching, image segmentation & matting, video stabilization, etc.

General Course Information

Pre-Requisites: CS 202 or its equivalence
Schedule: TR 16:40-18:30, Zoom
Syllabus
Grading policy: Readings (30%) + Presentation (20%) + Project (50%)
Class Mailing List: course-CS-510-071-202202-group@pdx.edu and course-CS-410-067-202202-group@pdx.edu

Textbook
We do not require any textbooks for this class. But the following two books will be very helpful.
	Computer Vision: Algorithms and Applications, by R. Szeliski This book is available online. Please download its latest version.	Learning OpenCV: Computer Vision with the OpenCV Library, by Gary Bradski and Adrian Kaehler. Or its new version Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library By Adrian Kaehler and Gary Bradski These books provide not only a good reference to the OpenCV library, but also gives very good descriptions of a vast amount of vision algorithms.

Lectures* *Many of the lecture notes were modified from materials for similar classes taught at other universities by Professor Yung-Yu Chuang, Frédo Durand, Chuck Dyer, Marc Levoy, Steve Seitz, Li Zhang, and Dr. Stephen Chenney and Richard Szeliski. Without their generous help, this class could not have been developed.
Date	Topic	Notes	*Readings
W10: 06/02	Project presentation		No reading assignment
W10: 05/31	Project presentation
W9: 05/26	Paper presentations
W9: 05/24	Paper presentations Stereoscopic 3D II	PDF	Keystone Correction for Stereoscopic Cinematography Feng Liu, Yuzhen Niu, Hailin Jin IEEE 3D Cinematography, 2012 Nonlinear disparity mapping for stereoscopic 3D Manue Lang, Alexander Hornung, Oliver Wang, Steven Poulakos, Aljoscha Smolic, Markus Gross SIGGRAPH 2010
W8: 05/19	Stereoscopic 3D I	PDF	Production Rules for Stereo Acquisition Frederik Zilly, Josef Kluger, Peter Kauff Proceedings of IEEE, 2011 Looking Beyond Stereoscopic 3D's Revival Kirk L. Kroeker, Communications of the ACM, 2010
W8: 05/17	Video Stabilization II	PDF	Subspace Video Stabilization Feng Liu, Michael Gleicher, Jue Wang, Hailin Jin, and Aseem Agarwala, ACM Transactions on Graphics, 2011
W7: 05/12	Video Stabilization I	PDF	Full-Frame Video Stabilization with Motion Inpainting Matsushita, Yasuyuki and Ofek, Eyal and Ge, Weina and Tang, Xiaoou and Shum, Heung-Yeung. IEEE PAMI 2006 Content-Preserving Warps for 3D Video Stabilization Feng Liu, Michael Gleicher, Hailin Jin, and Aseem Agarwala SIGGRAPH 2009
W7: 05/10	Image Matting	PDF	Compositing Digital Images Tom Porter and Tom Duff. SIGGRAPH 1984 Blue screen matting Smith, Alvy Ray and Blinn, James F. SIGGRAPH 1996
W6: 05/05	Graph-cut based Image Editing	PDF	Lazy Snapping. Yin Li, Jian Sun, Chi-Keung Tang and Heung-Yeung Shum. SIGGRAPH 2004 "GrabCut": Interactive Foreground Extraction Using Iterated Graph Cuts Carsten Rother, Vladimir Kolmogorov, and Andrew Blake SIGGRAPH 2014
W6: 05/03	Image Segmentation	PDF	Normalized Cuts and Image Segmentation Shi and Malik. IEEE PAMI 2000. Intelligent scissors for image composition E. Mortensen and W. Barrett. SIGGRAPH 1995
W5: 04/28	Panorama III	PDF	Multiperspective Imaging Steven M. Seitz and Jiwon Kim. IEEE CG&A 2003 Photographing long scenes with multi-viewpoint panoramas. A. Agarwala, M. Agrawala, M. Cohen, D. Salesin, and R. Szeliski. ACM Trans. Graph., 25(3):853–861, 2006
W5: 04/26	Panorama II	PDF	Szeliski book, Chapter 9 Recognising Panoramas, M. Brown and D. G. Lowe , ICCV 2003 AutoCollage, C. Rother, L. Bordeaux, Y. Hamadi, A. Blake, SIGGRAPH 2006
W4: 04/21	Panorama I	PDF	Image Alignment and Stitching: A Tutorial. Chapter 2 and 4 R. Szeliski. Foundations and Trends in Computer Graphics and Vision, 2009 Creating full view panoramic image mosaics and texture-mapped models. R. Szeliski and H.-Y. Shum. SIGGRAPH 97
W4: 04/19	Relighting II: High Dynamic Range Imaging	PDF	Recovering High Dynamic Range Radiance Maps from Photographs Paul E. Debevec and Jitendra Malik, SIGGRAPH 1997. High Dynamic Range Digital Photography, G. Brown, RPS Journal, Nov. 2006 Burst photography for high dynamic range and low-light imaging on mobile cameras Samuel W. Hasinoff, Dillon Sharlet, Ryan Geiss, Andrew Adams, Jonathan T. Barron, Florian Kainz, Jiawen Chen, and Marc Levoy. SIGGRAPH Asia 2016
W3: 04/14	Relighting I: Tone Mapping	PDF	Interactive local adjustment of tonal values. Lischinski, Dani and Farbman, Zeev and Uyttendaele, Matt and Szeliski, Richard. ACM SIGGRAPH 06 Photographic tone reproduction for digital images. E. Reinhard, M. Stark, P. Shirley, and J. Ferwerda, SIGGRAPH 2012
W3: 04/12	Light and Color	PDF	Color2Gray: Salience-Preserving Color Removal. Amy A. Gooch, Sven C. Olsen, Jack Tumblin, and Bruce Gooch. SIGGRAPH 05 Robust color-to-gray via nonlinear global mapping. Yongjin Kim and Cheolhun Jang and Julien Demouth and Seungyong Lee. SIGGRAPH ASIA 2009 Color harmonization D. Cohen-Or, O. Sorkine, R. Gal, T. Leyvand, Y. Xu, SIGGRAPH 2006
W2: 04/07	Denoising	PDF	Video Enhancement using Per-pixel Virtual Exposures Eric P. Bennett and Leonard McMillan. SIGGRAPH 2005 A Non-local Algorithm for Image Denoising. Buades, A., Coll, B., Morel, J.-M. IEEE CVPR 2005 Accelerating Spatially Varying Gaussian Filters Baek, J., Jacobs, D. E. SIGGRAPH Asia 2010
W2: 04/05	Filter	PDF	^#Szeliski book: Chapter 3.2. Hybrid Images A. Oliva, A. Torralba, P.G. Schyns, SIGGRAPH 2006 Bilateral Filtering for Gray and Color Images C. Tomasi and R.Manduchi. IEEE ICCV 1998
W1: 03/31	Camera	PDF	Computational Cameras: Redefining the Image. Nayar, S.K.. IEEE Computer, 39(8), 2006
W1: 03/29	Class overview	PDF	The Edge of Computational Photography Keith Kirkpatrick, Communications of ACM, 62(7),2019 Photography's Bright Future K. Kroeker, Communications of ACM, 52(2), 2009 Computational Photography, B. Hayes, American Scientist 96, 2007
* You might need to be on the PSU network or have an ACM/IEEE account to download some of papers. ^#You cannot select readings from a book for your reading assignment.

Reading Assignments:

Each week, you will read a few papers posted in the course web page. Besides, you need to pick one of the papers you read, write and send a short summary to lizhan@pdx.edu every Thursday afternoon before 4:00 pm.
In your email, please follow the following format for the email subject.
CS 410-510 Reading: You full name + Week number + Paper Title.

Your summary should be concise, no more than 500 words, and write in the plain text format in your email directly. You need to address the following five questions. Please answer these questions one by one following the format below exactly.

1. What problem is addressed?
2. How it is solved?
3. The advantages of the presented method?
4. The limitations of the presented method?
5. Future work

In-class Presentation:

Giving a good technical talk is an important skill for CS students. Every student needs to present one technical paper in the class. The presentation should be around 30 minutes, including 3-5 minutes of Q & A.

Your presentation should include the following content.
1. Title
2. Introduction
3. Outline
4. Method
5. Experiments/Results
6. Conclusion

Below is a list of advices on how to prepare and give a good technical talk.

How to give a technical presentation (how to give a scientific talk), by Michael Ernst
Giving an Academic Talk, by Jonathan Shewchuk
Preparing and Giving a Good Talk, by Steven Swanson

Project:

You have the following three project options.

Option 1. Literature study
If you choose this option, you cannot work in group. You will read a rich set of papers on one of the topics in computational photography, and write a survey paper. This is an O.K. option for you to fulfill the course requirement. Personally, this is not very exciting.

Option 2. System development
If you choose this option, you can work in group. A good group size will be 1~2. Your project size should be proportional to the group size. You will be graded as a group. So be cautious when you form a group. You can pick an algorithm you are interested in and implement an easy-to-use system. This is a popular and interesting option.

Option 3. Research
If you choose this option, you can work in group. A good group size will be 1~2. Your project size should be proportional to the group size. You will be graded as a group. You can define a new problem and solve it. Or, you can develop a new solution to an existing problem. This is an exciting, but less popular option.

For all these options, a good way to look for topics is to look into recent SIGGRAPH/SIGGRAPH Asia/ICCV/CVPR/ECCV conference proceedings. We will also go over a range of topics in the first few lectures in our class.

Candidate Project Topics

Project Timeline:

04/14: Submit a project proposal to fliu@pdx.edu. In your email subject, put CS510-410 Project Proposal + Your name. If you work in group, only one member of the group needs to submit a copy and the proposal should list all the group members. Your summary need to be concise, less than 300 words.

Week 10: In-class project presentation. Each presentation will last 7 minutes, including 6 minutes of presentation and 1 minute of Q & A. A group project only needs to be presented once. Please plan your presentation carefully so that you can finish it within 7 minutes.

06/06: Submit your final project to fliu@pdx.edu. In your email subject, put CS510-410 Project Title+ Your name(s). If you work in group, only one member of the group needs to submit the project. Your submission needs to include your final project report, your code, your testing examples and your in-class project presentation slides. If you work on a literature study project, no code or examples are required. Please make sure that you zip everything into a single .zip package and send me a link to it for me to download. Please do not send the files directly to me.

Programming Resouces

1. OpenCV

2. OpenCV-Python Installation

3. Visual Studio, OpenGL, and FLTK tutorial

4. Matlab Tutorial for Image Processing and sample files, provided by Prof. C. Dyer and his TA Tuo Wang at the University of Wisconsin, Madison.