Computer Vision (EC 331) - Department of Computer Science

Course Title: Computer Vision
Course Code: EC 331
Credits: 3
Instructor: Dr. Nazar Khan
Semester: Fall, 2024
Location: FCIT, Allama Iqbal Campus, Room 9
Class Times: Mondays and Wednesdays, 10:15 AM - 11:45 AM 		Textbook:
Foundations of Computer Vision (FoCV)
by Antonio Torralba, Phillip Isola, and William T. Freeman.
MIT Press
April, 2024
Join Google Classroom 		FoCVcover

Welcome to the Computer Vision course page! Computer Vision is a field of AI that focuses on enabling machines to interpret and understand the visual world. In this course, you will study both the theoretical foundations and practical applications of computer vision techniques, exploring how algorithms can process, analyze, and extract meaningful information from images. This course covers the theory and practice of computer vision. Dive into image processing, neural networks, object recognition, and advanced techniques such as deep learning, 3D vision, and motion analysis.

Lectures

Lecture Topic Readings Tutorials & Evaluations
1 Introduction Ch 1 Setup a Python environment for CV
2 Looking at Images + Computer Vision and Society Ch 3, 4
3 Image Formation and Lenses Ch 5, 6 How to make a pinhole camera
Tutorial 1: Introduction
4 Cameras as Linear Systems + Color Ch 7, 8
  • See first 8 slides of this lecture on matrix and vector calculus. You may also see the video explanation of those slides.
  • See the Wiki page on matrix calculus from which we will use denominator-layout notation.
  • See pages xxvii, xxviii, xxx, and xxxi of the FoCV textbook.
 Quiz 1, Solution
Tutorial 2: Color Spaces
5 Introduction to Machine Learning Ch 9 Slides Tutorial 3: Linear Regression
6 Gradient-based Learning + Generalization Ch 10, 11 Slides, Slides
7 Neural Networks Ch 12, 13 Slides Tutorial 4: Neural Networks using PyTorch: Recognition of Handwritten Digits
8 Linear Image Filtering Ch 15 Quiz 2, Solution
Tutorial 5: Convolution
9 Blur Filters Ch 17
10 Image Derivatives Ch 18 Assignment 1
Deadline: 11:59 pm, November 27
11 Image Sampling Ch 20, 21 Quiz 3
12 Image Pyramids Ch 23 Assignment 2
Tutorial 6: Image Blending via Laplacian Pyramids
13 Convolutional Neural Networks Ch 24
14 Transformers Ch 26 Assignment 2
Deadline: 11:59 pm, January 5
15 Representing Images and Geometry Ch 38 Quiz 4
16 Estimating and Applying Spatial Transformations Ch 41
17 Camera Modelling and Calibration Ch 39
18 Stereo Vision Ch 40
21 Homographies Ch 41 Assignment 4
22 Single View Metrology Ch 42 Quiz 5
23 Learning to Estimate Depth from a Single Image Ch 43
24 Multiview Geometry and Structure from Motion Ch 44 Assignment 5
25 Motion Estimation Ch 46, 47 Quiz 6
26 Optic Flow Ch 48, 49
27 Object Recognition Ch 50
28 Conclusion

Grading

Assignments Project Quizzes Midterm Exam Final Exam
Weight 12% 8% 5% 35% 40%