Introduction to Computer Vision

Webinar Abstract

Computer Vision (CV) is an engineering discipline that aims to build computers that see. Thanks to the remarkable progress that the CV community has achieved both in theory and applications, CV is applied in many different fields. For example, in the medical field, X-ray, CT, and MRI images are processed by CV tools to assist physicians to take the right decision at the right time. Similarly, satellite images are analyzed for military and civilian purposes. Given the large body of literature that CV community produces every year and with the existence of many different ways to mathematically formulate the same CV problem, it is always a challenge for new graduate students to find where to start. Hopefully, this lecture will help in finding this start point. More specifically we will describe a model based approach for CV where principals of probabilistic models, learning and inference are applied to formulate and solve many different CV problems in a unified framework. This lecture is for advanced undergraduate, graduate students, and serious CV practitioners.