Computer Vision

Term 2, Winter Session 2019-2020

This course was an introduction to the processing and interpretation of images. We learned about developments in image sensing, sampling, and filtering and were able to implement some techniques ourselves. We progressed from programmatic image manipulation to using machine learning for image recognition.

This is from an assignment where I implemented a key point recognition algorithm that was able to identify a unique set of points within a larger context.

This is an example image for Label 0.0 (category=Bedroom) in the confusion matrix below.

This is the confusion matrix result for one of the SVM models created based on the provided dataset of images and categories, 14 total.

Weekly individual assignments were in Python and covered a range of topics: image processing, interpretation, sampling, filtering, stereo imaging, panorama image creation, motion interpretation, and texture synthesis.