CENG 391
Introduction to Image Understanding
This course covers the basic image processing techniques and approaches for image content analysis.. The course content includes memory representation of images, basic image processing techniques, keypoint extraction and description, image matching and fundamentals of camera geometry.
Course Objectives
The main aim of the course is to familiarize the students with image processing and image content analysis. The course’s target audience is advanced undergraduate and beginning graduate students. The course will play a preparatory role for the graduate courses covering topics such as digital image processing and 3D photography.
Recommended or Required Reading
Computer Vision: Algorithms and Applications, R. Szeliski, 2010
Learning Outcomes:
To be able to apply image analysis methods to industrial problems
To be able to compare different image content analysis methods for a given problem
To be able to use basic image processing methods in problem solving
To be able to list basic image processing methods and their features
| Topics |
| Introduction |
| Image Representation |
| Basic Image Processing |
| Image Pyramids |
| Keypoint Detection |
| Keypoint Description and Matching |
| Planar Projective Geometry |
| Optimization Techniques |
| Image Matching |
| Optical Flow and Template Tracking |
| Basic Camera Geometry |
| Epipolar Geometry |
| Dense Image Features |
| Object Category Detection |