Introduction To Computer Vision

A Repository of projects, assignments and tutorials for ECSE 415, a class at McGill University.

Class Overview:

An introduction to the automated processing, analysis, and understanding of image data. Topics include image formation and acquisition, design of image features, image segmentation, stereo and motion correspondence matching techniques, feature clustering, regression and classification for object recognition, industrial and consumer applications, and computer vision software tools.

Technologies used:

• OpenCV
• TensorFlow
• Skimage

Assignments Breakdown:

• Assignment 1 : Image Filtering using thersholding, Sobel edge detection, Canny Edge detecto, Laplacian of Gaussian
• Assignment 2 :
Finding Image Feture descriptors using SIFT
• Assignment 3 :
Clustering using K-means, Expectation Maximization and Graph-Cut using MeanShift
• Assignment 4 :
Feature extraction in order to classify and predict image types
• Final Project : Facial Recognition project worked on with 4 other engineering students