CSE 590: Computational Photography
Instructor: Tamara Berg (tlberg -at- cs.sunysb.edu)
Office: 1411 Computer Science
Lectures: Mon 11:30am-2:30pm, Rm 2129 CS
Office Hours: Mon 3:00-5:00pm (and by appointment)
Course Webpage: http://tamaraberg.com/teaching/Fall_11

Introduction
This course will explore topics in computational photography, a field at the intersection of computer vision, graphics, and photography. Over the semester we will look at how computation can be used to capture, create, and enhance digital imagery in an effort to move beyond the constraints of traditional cameras. Main areas covered will include: a) images, manipulation, and editing, b) exploiting large corpora, and c) the computational camera.

MS Basic Project Option

Sign up as CSE 522 to complete the MS Basic Project Option

Schedule (subject to change)

Date Topic Readings (S=Szeliski book) Assignments

Aug 29 No class (hurricane) - -
Sept 5 No class (labor day) S3.2-3.4 HW1 - image alignment - due Sept 18
Sept 12 Intro & Basics of images, pixels and pyramids - Slides, Demos (compphotog.m) S3.5.2, S8.1.1, Burt Adelson 1983 - The Laplacian Pyramid -
Sept 19 Compositing, Blending, & Resizing - Slides Poisson Image Editing,
Seam Carving for Content-Aware Image Resizing,
Interactive Digital Photomontage HW2 - due Oct 2
Sept 26 Cutting & Growing - Slides GrabCut,
Texture Synthesis -
Oct 3 Warping & Morphing - Slides S3.6, View Morphing HW3 - due Oct 16
Oct 10 Project Proposals & Image Stitching for Panoramas - Slides S9, AutoStitch 5 minute presentation
Oct 17 Big Data Intro - Slides 80 Million Tiny Images,
Scene Completion Using Millions of Photographs,
Creating and Exploring a Large Photorealistic Virtual Space HW4 - due Oct 30
Oct 21 Computational Photography - Talk (Humanities Center) - Chris Bregler, NYU
Oct 24 Big Data Places Photo-Tourism,
Im2GPS,
Photo Pop-Up -
Oct 31 Big Data People Exploring Photobios,
Being John Malkovich -
Nov 7 Project Updates & Group meetings - 10 minute presentation
Nov 14 Intro to cameras, color & light - -
Nov 18 Computational Photography DLS Talk (CEWIT) - Bill Freeman, MIT
Nov 21 The Computational Camera, 3D & the Kinect Light Field Photography with a Hand-held Plenoptic Camera,
Image and Depth from a Conventional Camera with a Coded Aperture,
Real-Time Human Pose Recognition in Parts from a Single Depth Image -
Nov 28 Final Project Presentations - Final Presentation
Dec 5 David Forsyth (guest lecture) "Rendering Synthetic Objects into Legacy Photographs" - Video Note: Class will be held in 2311 CS
Dec 15 Final Project Write-Up - Final Project Write-Up Due - 8 page document including abstract, introduction, method, results & figures

Grading
There will be 4 homeworks during the first few months of the course to get students aquainted with computational photography. Over the final few months of the course students will develop and present a project related to computational photography. There will also be approximately 4 in class quizzes over the course of the semester.

Grading breakdown: Assignments (40%), Project (30%), Quizzes (20%), participation (10%),
Late homeworks will be accepted with 10% penalty per day.

No prior experience in computer vision or graphics is required to take this course. Homeworks must be done individually, but projects may be done in pairs. Homeworks are recommended to be completed in matlab. Projects may be done in matlab or language of student's preference.

Submit all homeworks and project presentations to: sbu590@gmail.com

Text Book
Computer Vision: Algorithms and Applications by Rick Szeliski (draft)

Other Reference Books
Forsyth, David A., and Ponce, J. Computer Vision: A Modern Approach, Prentice Hall, 2003.
Hartley, R. and Zisserman, A. Multiple View Geometry in Computer Vision, Academic Press, 2002.

Matlab
Student Matlab licenses can be purchased from mathworks for $99 - Link.
Matlab tutorial by Hany Farid and Eero Simoncelli - Link
A more comprehensive Matlab tutorial by David Griffiths - Link

Credits
Many thanks to Alyosha Efros for excellent course and project design. Also thanks to Derek Hoeim, James Hays and others for their computational photography course materials, slides, etc.

Americans with Disabilities Act: If you have a physical, psychological, medical or learning disability that may impact your course work, please contact Disability Support Services, ECC (Educational Communications Center) Building, room 128, (631) 632-6748. They will determine with you what accommodations, if any, are necessary and appropriate. All information and documentation is confidential.

Academic Integrity: Each student must pursue his or her academic goals honestly and be personally accountable for all submitted work. Representing another person's work as your own is always wrong. Faculty are required to report any suspected instances of academic dishonesty to the Academic Judiciary. Faculty in the Health Sciences Center (School of Health Technology & Management, Nursing, Social Welfare, Dental Medicine) and School of Medicine are required to follow their school-specific procedures. For more comprehensive information on academic integrity, including categories of academic dishonesty, please refer to the academic judiciary website at http://www.stonybrook.edu/uaa/academicjudiciary/

Critical Incident Management: Stony Brook University expects students to respect the rights, privileges, and property of other people. Faculty are required to report to the Office of Judicial Affairs any disruptive behavior that interrupts their ability to teach, compromises the safety of the learning environment, or inhibits students' ability to learn. Faculty in the HSC Schools and the School of Medicine are required to follow their school-specific procedures.