Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
1AIN434Fundamentals of Computational Photography3+0+03612.08.2025

 
Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program ARTIFICIAL INTELLIGENCE ENGINEERING
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course Computation photography is an emerging new research area which brings together the advancements in computer graphics, computer vision and image processing to overcome the limitations of conventional photography. The subject matter of this course is to provide an introduction to key topics in computational photography.
Course Content Cameras and image formation
Color perception
Image processing review
Data-driven image synthesis
Image manipulation (warping, morphing, mosaicing, matting, blending, compositing),
Panoramas, mosaics and collages
Denoising
Image inpainting
High dynamic range imaging and tone mapping
Depth and defocus
Image-based lighting and rendering
Non-photorealistic rendering.
Course Methods and Techniques Lecture, Problem Solving
Prerequisites and co-requisities ( BBM102 ) and ( BBM104 ) and ( AIN435 )
Course Coordinator None
Name of Lecturers Associate Prof. Erkut Erdem
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Photography (9th edition), Barbara London, Jim Stone, and John Upton, Pearson, 2007; Computer Vision: Algorithms and Applications, Richard Szeliski, Springer, 2010
Course Notes Photography (9th edition), Barbara London, Jim Stone, and John Upton, Pearson, 2007

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


Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Midterm Exam 1 % 30
Attendance 1 % 5
Project 1 % 25
Final examination 1 % 40
Total
4
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 3 42
Hours for off-the-c.r.stud 14 4 56
Project 1 45 45
Preparation for Midterm Exam 1 15 15
General Exam Preparation 1 20 20
Total Work Load   Number of ECTS Credits 5,93333333333333 178

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 After completing the course, the students will study techniques to capture digital images and videos;
2 have a deep understanding about computational methods to manipulate and enrich visual media;
3 read and discuss some research papers from the current literature.
4  
5  
6  
7  
8  

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction
2 Cameras and image formation
3 Color perception
4 Image processing review
5 Data-driven image synthesis
6 Image manipulation (warping, morphing, mosaicing, matting, blending, compositing),
7 Panoramas, mosaics and collages
8 Midterm exam
9 Denoising
10 Image inpainting
11 High dynamic range imaging and tone mapping
12 Depth and defocus
13 Image-based lighting and rendering
14 Non-photorealistic rendering
15 Preparation for Final Exam
16 Final exam

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
All 4 4 2 4 3 3 3 4 3 2 2 4
C1
C2
C3
C4
C5
C6
C7
C8

  Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

  
  https://bilsis.hacettepe.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=2733667&lang=en