Tuesday, 17.11.2015, 11:30
Defining and calculating similarity between objects or images is one of the key topics in computer vision and computer graphics. After reviewing my early work on similarity for shape analysis, I will present my recent work, which focuses on the human EYE. The eye is the only organ in the body where one can non-invasively image blood vessels and nerve tissue. Thus, in addition to detecting eye-specific conditions, by looking into the eye we can diagnose systemic diseases, such as heart disease, stroke threats, diabetes, Alzheimer’s and multiple sclerosis. First, I will talk about prediction of eye fixations when watching RGBD video. Then, I will discuss the holy grail of the modern healthcare, disease prediction, in our case, prediction based on the photo of the eye. I will show how similarity between eye images can assist computer vision and machine learning algorithms to perform early screening and even disease prediction.
George Leifman earned his three academic degrees (BSc, MSc, PhD) from the Faculty of Electrical Engineering at the Technion. His master thesis was co-supervised by Prof. Ayellet Tal and Prof. Ron Meir and his doctoral research was supervised by Prof. Ayellet Tal. Currently, George is a Post-Doctoral Fellow at the Media Lab, MIT.