Introduction

This is an introductory course on computer vision and computational photography. This course will explore image formation, image features, image segmentation, image stitching, image recognition, motion estimation, 3D point clouds and will touch upon basics of augmented reality.

For further information, please see the course syllabus.

General Information

Class Time Tuesdays & Thursdays 9:30AM - 10:45AM Location CSI 2117         Instructor Yiannis Aloimonos Email yiannis@cs.umd.edu Office AVW 4475 Office Hours TBD     Name Jack Rasiel Email jrasiel@cs.umd.edu Office AVW 4103 Office Hours MW 3-5PM     Name Kaan Elgin Email kelgin@cs.umd.edu Office TBA Office Hours TH 2:30-4:30PM, F 2:30-4:30PM

Piazza

Important class announcements will be made through the Piazza system. The class Piazza can be found here.

Acknoledgements

Special thanks to Dr. Cornelia Fermüller for providing most of the lecture materials for this class.

A lot of projects in this course are based on graduate and doctoral courses from other universities. Links to these courses can be found in the Logistics section under the title Other Good Computer Vision Courses and Tutorials.

The course website is based on Prof. David Mount's website for CMSC 754: Computational Geometry found here. We loved the simplicity and lightness of his website design.

Some Useful Resources

The links to e-books of the reference books if available are given in the Logistics section under the title Reference Books.

Online resource of computer vision topics (contains short descriptions and tutorials on basic and advanced topics)

Image Processing Learning resources

Image Processing Online Journal. Contains many good algorithms with implementations for free.

MATLAB Speed Up Tricks

Image Filtering Tutorial

Peter Kovesi's awesome computer vision and image processing functions for MATLAB. Literally has everything you need.

VLFeat for MATLAB. Has a lot of new algorithms and supports all platforms.

Peter Corke's Machine Vision Toolbox for MATLAB. Has a lot of new algorithms and supports all platforms.

Some slides for using MATLAB in Image Processing from ETH Zurich

MATLAB tutorial from University of Toronto