Computational Photography
Spring 2020
Instructor: Nima Kalantari

Course information

Time and location: MWF 10:20 - 11:10 pm in 113 HRBB
Office hours: TTh 2:00 - 3:00 pm
Office location: 527B HRBB
Email: nimak@tamu.edu
Piazza: https://piazza.com/tamu/spring2020/csce489689c/

TA: Avinash Paliwal
Email: avinashpaliwal@tamu.edu
Office hours: MW 3:00 - 5:00 pm
Office location: EAB-C 118C

Overview

Computational photography is a collection of computational algorithms and system designs (e.g., sensors, optics) to avoid the limitations of standard cameras and enable novel applications. In recent years, there has been increasing interest in computational photography because of the widespread use of the cameras by the general public through smartphones and other cheap imaging devices. In this course, we first discuss the cameras and the image formation process. We then study basic image and video processing tools like sampling, filtering, and pyramids. Finally, we discuss several image-based algorithms, such as image retargeting, high dynamic range imaging, and texture synthesis.

Prerequisites

CSCE 315 and MATH 304. Graduate students are expected to have similar background.

Textbook

The primary reference of the course is the following book, which covers most of the topics related to computational photography:

Computer Vision: Algorithms and Applications, by Richard Szeliski, 2010

Grading

Late Submissions

You will lose 20% from each assignment for each day that it is late. However, there will be 5 granted late days for the entire course. You are free to use it for any of the assignments (note that, you CANNOT use it for the final project!). You will not get any bonuses for any of the unused late days. All the assignments are due at 11:59 pm on ecampus unless otherwise stated. Note that, one minute over and 23 hours over both count as one full day.

Academic Integrity

The assignments in this class are individual unless otherwise stated. For the individual assignments, all the codes need to be written by the student. If indicated in the assignment’s instruction, the use of external libraries for performing basic operations is allowed. However, using an outside source code is NOT permitted. Moreover, collaborating with other students on assignments beyond general discussions is NOT allowed. In general, looking at other students’ code and/or written answers is NOT allowed. If the students have any questions regarding this issue, they should contact the instructor. The students should not post their code online even after the deadline for the assignment has passed.

Schedule*

Date Topic Slides Reading Assignments
Jan 13 Introduction and Overview pdf, pptx Szeliski Ch. 1
Jan 15 Camera and Image Formation pptx Szeliski Ch. 2 HW 1 Out
Jan 17 Camera and Image Formation See above Szeliski Ch. 2
Jan 20 MLK Day - No Class
Jan 22 Camera and Image Formation See above Szeliski Ch. 2
Jan 24 Color
Jan 27 Color HW 1 Due
Jan 29 Sampling and Filtering
Jan 31 Sampling and Filtering
Feb 3 Frequency Domain
Feb 5 Frequency Domain
Feb 7 Pyramids
Feb 10 Blending and Compositing
Feb 12 Blending and Compositing
Feb 14 Point Processing and Image Warping
Feb 17 Point processing and Image Warping
Feb 19 Homographies and Mosaics
Feb 21 Automatic Image Alignment and RANSAC
Feb 24 Automatic Image Alignment and RANSAC
Feb 26 Stereo
Feb 28 Stereo
Mar 2 Camera Parameters
Mar 4 Modeling Light and Lightfields
Mar 6 Modeling Light and Lightfields
Mar 9 - 13 Spring break - No Class
Mar 16 Image Retargeting
Mar 18 Image Retargeting
Mar 20 High Dynamic Range Imaging
Mar 23 High Dynamic Range Imaging
Mar 25 Tonemapping and Exposure Fusion
Mar 27 Fast Bilateral Filter
Mar 30 Matting
Apr 1 Midterm Review
Apr 3 Midterm Exam
Apr 6 Image Morphing
Apr 8 Video Textures
Apr 10 Reading Day - No Class
Apr 13 Texture Synthesis and Filling
Apr 15 Midterm Solution
Apr 17 Image Analogies and Scene Completion
Apr 20 Image Analogies and Scene Completion
Apr 22 Coded Exposures and Apertures
Apr 24 Coded Exposures and Apertures
Apr 27

*Schedule might change during the semester.

Acknowledgements

The slides in this class are heavily based on the slides from other instructors. Specifically, many slides are the exact or modified version of the slides by Alexei A. Efros, James Hays, and Rob Fergus, who in turn have used materials from Steve Seitz, Rick Szeliski, Paul Debevec, Stephen Palmer, Paul Heckbert, David Forsyth, Steve Marschner, Fredo Durand, Bill Freeman, and others, as noted in the slides. The instructor gives full permission to use these slides for academic and research purposes, but please maintain all the acknowlegements.