“ But one must learn to read, just as one must learn to see and learn to live. ” - Vincent Van Gogh, from Letters to Theo
Computer vision aims to develop methods that enable machines to gain the ability to analyze and understand the visual inputs. This undergraduate level course is intended for introducing the fundamental topics of computer vision. In this context, we will first start from the low-level image perception aspects, such as image formation, cameras, color and continue with mid-level vision topics, such as interest point detection and local feature extraction. The course will also introduce the fundamentals of high-level vision tasks, such as face detection/recognition, object recognition and human motion analysis.
Prerequisites: linear algebra, basic knowledge of probability and statistics, good programming skills.
Instructor: Nazli Ikizler Cinbis , nazli -at- cs.hacettepe.edu.tr
Office: 112, Office Hours: Thursdays 10:00-12:00
Lecture Hours: Fridays 09:00-11:45
Lecture Room: D8
Project: The project will involve designing and implementing a computer vision system towards solving a fundamental vision problem. The project can be carried out individually or in groups of two. In the context of BBM418 Computer Vision Laboratory, the students are required to complete four programming assignments.
Date | Topic | Slides | Readings | Assignments |
March 8th | Introduction to computer vision | .ppt | Szeliski 1 | |
March 15th | Image formation, camera and color | .ppt | Szeliski 2, FP 1.1,3.1,3.3 | Assignment 1 out |
March 22nd | Filters, Templates and Image Pyramids | .ppt | Szeliski 3.2, FP 4 | |
March 29th | Interest points and image features | .ppt | Szeliski 4.1, FP 5 | Assignment 1 due, Assignment 2 out |
April 5th | Edge Detection, line fitting | .ppt | Szeliski 4.1, FP 8 | |
April 12th | Machine learning: clustering and classification overview | .ppt | Szeliski 5 | Assignment 2 due |
April 19th | Midterm Exam | |||
April 26th | Instance recognition, bag-of-words models | .ppt | Szeliski 14.2, Szeliski 14.3, FP 16 | Assignment 3 out |
May 3rd | Object detection with sliding windows | .ppt | Szeliski 14.1, FP 17 | |
May 10th | Motion analysis and Tracking | .ppt | FP 11 | Assignment 3 due |
May 17th | Human Action Recognition | .ppt | Assignment 4 out | |
May 24th | Image Retrieval | .ppt | FP 21 | |
May 31th | Advanced Applications | .ppt | Final Project due | |
June 6th | Project presentations | Assignment 4 due |