Simon Fraser University
Engaging the World

Course Outlines

Spring 2021 - CMPT 461 D100

Computational Photography and Image Manipulation (3)

Class Number: 7020

Delivery Method: In Person

Overview

  • Course Times + Location:

    Jan 11 – Apr 16, 2021: Tue, 2:30–4:20 p.m.
    Burnaby

    Jan 11 – Apr 16, 2021: Fri, 2:30–3:20 p.m.
    Burnaby

  • Exam Times + Location:

    Apr 19, 2021
    Mon, 8:30–11:30 a.m.
    Burnaby

  • Prerequisites:

    CMPT 361, MACM 201 and 316.

Description

CALENDAR DESCRIPTION:

Computational Photography is concerned with overcoming the limitations of traditional photography with computation: in optics, sensors, and geometry; and even in composition, style, and human interfaces. The course covers computational techniques to improve the way we process, manipulate, and interact with visual media. The covered topics include image-based lighting and rendering, camera geometry and optics, computational apertures, advanced image filtering operations, high-dynamic range, image blending, texture synthesis and inpainting. Students with credit for CMPT 451 may not take this course for further credit.

COURSE DETAILS:

Computational Photography is concerned with overcoming the limitations of traditional photography with computation: in optics, sensors, and geometry; and even in composition, style, and human interfaces. The course covers computational techniques to improve the way we process, manipulate, and interact with visual media. The covered topics include image-based lighting and rendering, camera geometry and optics, computational apertures, advanced image filtering operations, high-dynamic range, image blending, texture synthesis and inpainting.

COURSE-LEVEL EDUCATIONAL GOALS:

Topics

  • · Imaging basics
  • · Camera basics
  • · Fourier transform and sampling
  • · High dynamic range imaging
  • · Tone mapping
  • · Bilateral filtering
  • · Color
  • · Image blending
  • · Boundary minimization techniques
  • · Focal stacks and light fields
  • · Transformations and panoramas
  • · Camera models
  • · Optical flow
  • · Deconvolution and noise

Grading

NOTES:

· Programming assignments: 30% · Final project: 40% · Presentation: 30%

Materials

RECOMMENDED READING:

  • Computer Vision: Algorithms and Applications, , R. Szeliski, Springer London, 2011, 9781848829350

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html

TEACHING AT SFU IN SPRING 2021

Teaching at SFU in spring 2021 will be conducted primarily through remote methods. There will be in-person course components in a few exceptional cases where this is fundamental to the educational goals of the course. Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.

Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112).