Computational Models for Video Understanding

Amit K. Roy Chowdhury


Abstract

Tremendous progress has been made within the past decade in the collection, storage and transmission of video. However, the tools for analyzing the video and obtaining mathematical descriptions of the underlying content lag behind. In this presentation, I will focus on computational dynamical models that we have developed in order to represent the temporal evolution of a video sequence. Together with static image models that describe the object appearance, this provides a mathematical description for representing the video sequence. We will consider particular examples in human activity inference and human motion modeling to demonstrate the applicability of dynamical models in shape space using Kendall's statistical shape theory.


Maintained by Philippos Mordohai