CMU 15-463: Computational Photography


	15-463 (15-862): Computational Photography Computer Science Department Carnegie Mellon University

INSTRUCTOR: Alexei (Alyosha) Efros (Office hours: Tuesday 4:30-5:30, Smith 225)
TA: Ronit Slyper (Office hours: See our google group home page)
UNIVERSITY UNITS: 12
SEMESTER: Fall 2010
DISCUSSION GROUP: googlegroups (contact Ronit)
WEB PAGE: http://graphics.cs.cmu.edu/courses/15-463/
LOCATION: GHC 4301
TIME: T R 12:00--1:20 PM

COURSE OVERVIEW:
Computational Photography is an emerging new field created by the convergence of computer graphics, computer vision and photography. Its role is to overcome the limitations of the traditional camera by using computational techniques to produce a richer, more vivid, perhaps more perceptually meaningful representation of our visual world.

The aim of this advanced undergraduate course is to study ways in which samples from the real world (images and video) can be used to generate compelling computer graphics imagery. We will learn how to acquire, represent, and render scenes from digitized photographs. Several popular image-based algorithms will be presented, with an emphasis on using these techniques to build practical systems. This hands-on emphasis will be reflected in the programming assignments, in which students will have the opportunity to acquire their own images of indoor and outdoor scenes and develop the image analysis and synthesis tools needed to render and view the scenes on the computer.

TOPICS TO BE COVERED:

Cameras, Image Formation
Visual Perception
Image and Video Processing (filtering, anti-aliasing, pyramids)
Image Manipulation (warping, morphing, mosaicing, matting, compositing)
Modeling and Synthesis using Lots of Data
High Dynamic Range Imaging and Tone Mapping
Image-Based Lighting
Image-Based Rendering
Non-photorealistic Rendering

PREREQUISITES:
Programming experience and familiarity with linear algebra and calculus is assumed. Some background in computer graphics, computer vision, or image processing is helpful. This class does not significantly overlap with 15-462 and can be taken concurrently.
Graduate Students: a small number of graduate students will be allowed to take the graduate version of this course (15-862) with the permission of the instructor. Students taking 15-862 will be required to do more substantial assignments as well as a research-level final paper.
Note: if the system doesn’t let you sign up, or puts you on the waitlist, do talk to me.

PROGRAMMING ASSIGNMENTS:

· Project 0: Matlab Worksheets (ongoing)

class results
Class Choice Award: Billy Keyes

· Project 1: Images of the Russian Empire -- colorizing the Prokudin-Gorskii photo collection

class results
Class Choice Award: Josip Djolonga

· Project 2: Image Resizing by Seam Carving (for undergrads)

· Project 2g: Gradient Domain Editing (for grad students)

class results
Class Choice Award (undergrad): Josip Djolonga
Class Choice Award (grad): Scott Griffith and You Jia

· Project 3: Face morphing and modeling:

class results

· Project 4: Stitching Photo Mosaics (all)

· Project 4g: Single-View Reconstruction (grad students only)

Class Choice Award (undergrad): Junjie Liang
Class Choice Award (grad): Nick Vandal
class results

Final Projects!

TEXT:
Since Computational Photography is such a new discipline, no comprehensive textbook exists for use in the class. Therefore, there is no required text. Various course notes and papers will be made available. We will also use the following almost-finished textbook (available online) as reference:

Computer Vision: Algorithms and Applications, Richard Szeliski

There is a number of other fine texts that you can use for general reference:

Computer Vision: The Modern Approach, Forsyth and Ponce
Photography (8^th edition), London and Upton, (a great general guide to taking pictures)
Vision Science: Photons to Phenomenology, Stephen Palmer (great book on human visual perception)
Science for the Curious Photographer, Charles Johnson (an fun and easy read)
Digital Image Processing, 2nd edition, Gonzalez and Woods (a good general image processing text)
The Art and Science of Digital Compositing, Ron Brinkmann (everything about compositing)
Multiple View Geometry in Computer Vision, Hartley & Zisserman (a bible on recovering 3D geometry) [on reserve]
The Computer Image, Watt and Policarpo (a nice “vision for graphics” text, somewhat dated)
3D Computer Graphics (3rd Edition), Watt (a good general graphics text)
Fundamentals of Computer Graphics, Peter Shirley (another good general graphics text)
Linear Algebra and its Applications, Gilbert Strang (a truly wonderful book on linear algebra)

CLASS NOTES
The instructor is extremely grateful to a large number of researchers for making their slides available for use in this course. Steve Seitz and Rick Szeliski have been particularly kind in letting me use their wonderful lecture notes. In addition, I would like to thank Paul Debevec, Stephen Palmer, Paul Heckbert, David Forsyth, Steve Marschner, Fredo Durand and others, as noted in the slides. The instructor gladly gives permission to use and modify any of the slides for academic and research purposes. However, please do also acknowledge the original sources where appropriate.

CLASS SCHEDULE:

CLASS DATE	TOPICS	Material
Tu Aug 24	Introduction	Slides (ppt , pdf)
Th Aug 26	Capturing Light… in man and machine	Slides (ppt , pdf)
Tu Aug 31	Sampling and Reconstruction	Slides (ppt , pdf)
Th Sept 2	The Frequency Domain	Slides (ppt , pdf)
Tu Sept 7	Point Processing (by Ronit)
Th Sept 9	NO CLASS
Th Sept 14	Continue with Freq. Domain: gradients, frequency perception, compression, morphology
Th Sept 16	Image Blending and Compositing	Slides (ppt , pdf) Additional Reading: Burt and Adelson, A multiresolution spline with application to image mosaics, ACM ToG (1983) McCann & Pollard, Real-Time Gradient-Domain Painting, SIGGRAPH 2008 Agarwala et al, Interactive Digital Photomontage, SIGGRAPH 2004
Tu Sept 21	Image Warping	Slides (ppt , pdf)
Tu Sept 28	Image Morphing	Slides (ppt , pdf)
Th Sept 30	Data-driven Methods: Faces	Slides (ppt , pdf) · Rowland and Ferrett, “Manipulating Facial Appearance through Shape and Color”, CG&A, 1995 · Additional Reading: Blanz and Vetter, “A Morphable Model for the Synthesis of 3D Faces”, SIGGRAPH 1999 Cootes, Edwards, and Taylor, “Active Appearance Models”, ECCV 1998
Tu Oct 5	Data-driven Methods: Video and Texture	Slides (ppt , pdf) Reading: Schold et al, Video Textures, 2000 Reading: Efros & Lreung, Texture Synthesis by Non-parametric Sampling, 1999 Additional Reading: Image Analogies
Th Oct 7	Data-driven Methods: Features, Histograms, and Image Comparisons	Slides (ppt , pdf)
Tu Oct 12	Data-driven Methods: Internet Data	Reading: Hays & Efros, Scene Completion Using Millions of Photographs Additional Reading: 1. im2gps 2. Creating and Exploring a Large Photorealistic Virtual Space
Th Oct 14	The Camera	Slides (ppt , pdf)
Tu Oct 19	Modeling Light	Slides (ppt , pdf)
Th Oct 21	Homographies and Mosaics	Slides (ppt , pdf) Paul Heckbert, Projecting Mappings for Image Warping Project #4 OUT
Sun Oct 24	More Mosaic Madness	· Slides (ppt , pdf) · Additional Reading: Rick Szeliski, Image Alignment and Stitching, A Tutorial (DRAFT)
Th Oct 28	Automatic Alignment	Slides (ppt , pdf) Reading: Brown et al, “Multi-Image Matching using Multi-Scale Oriented Patches”, CVPR 2005 Reading: M. Brown and D. G. Lowe. Recognising Panoramas (ICCV2003) (pdf 820kb) Reading: RANSAC
Tu Nov 2	Multi-perspective Panoramas	Slides (ppt, pdf) Reading: Squaring the Circle in Panoramas Reading: Automating joiners Additional Reading: Photographing long scenes with multi-viewpoint panoramas Additional Reading: Scene Collages and Flexible Camera Arrays Flickr: http://flickr.com/groups/joiners/
Th Nov 4	Single View Reconstruction	· Slides (ppt, pdf) · Reading: Horry et al, “Tour into the Picture”, SIGGRAPH ‘97
Tu Nov 9	More Single View Geometry	· Slides (ppt, pdf) · Additional Reading: Single-view Reconstruction