Vision and Robotics Seminar Amnon Shashua School of Computer Science \& Engineering Hebrew University will speak on Learning over instance spaces made out of sets with application to video sequence interpretation Abstract: The talk is about developing a similarity function that operates on pairs of sets of vectors --- where a vector can represent an image and a set of vectors could represent a video sequence for example --- in such a way that the function can be plugged into a variety of existing classification engines. The crucial ingredients are therefore (i) the function can be evaluated in high dimensional spaces using simple functions (kernel functions) evaluated on pairs of vectors in the original (relatively low-dimensional) space, and (ii) the function describes an inner-product space, i.e., is a positive definite kernel. We will be using two running examples to motivate and test the ideas described in the talk. The first task is the discrimination of ``suspicious'' motion of an individual or a group of individuals in a video sequence. We use the SVM approach using our similarity function defined over matrices where an input matrix represents the motion trajectory of a group of individuals over a certain (fixed) time frame. We show that the classification (suspicious versus non-suspicious) greatly outperforms the conventional representation of forming a single vector out of all the trajectories. The second application is the visual recognition of f aces from input video sequences representing head motion and facial expressions. This work is co-authored with Lior Wolf. The lecture will take place in the Lecture Hall, Room 1, Ziskind Building on Thursday, November 14, 2002 at 11:00