Special Topics in Computer Vision
Second semester 2019
Andrés Marrugo, PhD
Universidad Tecnológica de Bolívar
Aims and Scope
This course discusses advanced topics and current research in computer vision. Students are expected to read papers selected from various subareas such as 3D reconstruction, machine vision and inspection, segmentation and grouping, and pattern recognition. Approaches for learning from image data will be covered and include topics from convolutional neural networks, sparse and redundant representations, and others. The course will be a mix of lecture, student presentation and discussion.
Course Goals:
- Gaining research experience in computer vision.
- Get exposed to a variety of topics and become familiar with state-of-the-art techniques.
- Learn to read and evaluate other people’s work.
- Get hands dirty on a research project.
Useful Resources
Tutorials, review materials
- MATLAB tutorial
- More MATLAB tutorials: basic operations, programming, working with images
- Linear algebra review
- Random variables review
MATLAB reference
Outline
This is a new course, this website will be updated as we go along.
Lecture 1: Introduction
We will be discussing the general aspects of the course, the topics to be covered and the course project.
Paper review 1 - Non local means
Paper reviews. Due date: 2019-08-27.
Paper review 2 - The world’s most famous camera calibration method
Paper reviews. Due date: 2019-09-3.
Paper review 3 -
Paper review 4 -
Paper review 5 -
Paper review 6 -
Project submission
The project final report is due Friday, December 6. Use the following link to upload the paper (in IEEE template or similar) and a 3 minute video of yourselves explaining the project.