Statistical problems in computer vision
Seminar Room 1, Newton Institute
Computer vision is one of the many fields that successfully adopted machine learning for
building predictive models. Yet, despite their success some of the fields' most popularly
used models such as conditional random fields remain poorly understood theoretically
and require approximations to be practical. I discuss a few of open theoretical and
practical questions in these models in the computer vision context.