Spring 2025 - CMPT 461 D100
Computational Photography and Image Manipulation (3)
Class Number: 5464
Delivery Method: In Person
Overview
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Course Times + Location:
Jan 6 – Apr 9, 2025: Tue, 8:30–10:20 a.m.
BurnabyJan 6 – Apr 9, 2025: Fri, 8:30–9:20 a.m.
Burnaby
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Instructor:
Yagiz Aksoy
yagiz@sfu.ca
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Prerequisites:
CMPT 361 with a minimum grade of C-.
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 intrinsic decomposition, monocular depth estimation, edit propagation, camera geometry and optics, computational apertures, advanced image filtering operations, high-dynamic range, image blending, texture synthesis and inpainting.
COURSE DETAILS:
Modern computational photography takes its powers from computer vision methods that works at high resolutions in-the-wild and applies them to re-render new photographs using techniques in computer graphics. This course covers computational photography from practical and theoretical perspectives. Students will get an overview of classical and modern formulations in computational photography research and also develop custom practical applications. In the first few weeks, we cover fundamental computational photography concepts, formulations, and applications and also in real-world film production environments through guest lectures. The latter part of the course follows a curriculum focused on recent/current research. 2 hours of each week is dedicated to deep dives to fundamental topics in image manipulation including monocular depth estimation, intrinsic decomposition, soft segmentation and alpha matting, image recoloring, and more. 1 hour each week is reserved for all-together open-ended discussions on term projects and research papers. Students form project groups and each projects develops their own photography project through discussions with the instructor. Each student also prepares a detailed video presentation of a selected research paper, which is watched and discussed together in class at the end of the semester. The collaboration is enhanced through weekly check-ins and discussions during lecture hours. Attendence to lectures, with in-person and Zoom options, are mandatory for the entire semester.
Grading
- Group project 50%
- Paper discussion and video 30%
- Programming assignments 20%
REQUIREMENTS:
Background on image processing and computer vision (CMPT 361)
Materials
REQUIRED READING NOTES:
Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.
Registrar Notes:
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
SFU’s Academic Integrity website 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
RELIGIOUS ACCOMMODATION
Students with a faith background who may need accommodations during the term are encouraged to assess their needs as soon as possible and review the Multifaith religious accommodations website. The page outlines ways they begin working toward an accommodation and ensure solutions can be reached in a timely fashion.