Tel-Aviv University - Computer Science Colloquium

Sunday, Jan 22, 2006, 11:15-12:15

Room 309
Schreiber Building


Lihi Zelnik-Manor



Analysis of Dynamic Visual Information



Dynamic scenes captured by a moving camera generate rich and complex visual

data. To understand the content of such videos, one needs to be able to

extract the relevant information from the raw data, separate between its

independent parts and recognize pieces of similar content. I will start by

presenting a subspace-based approach to modeling rigid and non-rigid motion

in a video sequence. I will then show how the suggested representation can

be used for a variety of tasks, including motion based spatial segmentation,

expression recognition, sequence-to-sequence synchronization and more. These

applications often require clustering tools that operate on affinity

relations which are pairwise or of higher order. I will propose new

clustering algorithms and appropriate data representations accompanied by

empirical results on real video sequences.