A Selective Overview of Graph Cut Energy Minimization Algorithms Ramin Zabih Cornell University While many important vision problems can be phrased in terms of energy minimization, it is only recently that efficient algorithms have been developed. I will present some highlights of the work on graph cut algorithms, focusing on results that are due to my students. In particular, I will highlight the role of problem reducability, and describe a relatively simple way to apply graph cuts to an energy minimization problem. Bio: Ramin Zabih is an Associate Professor of Computer Science at Cornell University. He did his undergraduate work at MIT, and received his PhD from Stanford in 1994. He is best known for his work on the use of graph cut algorithms in computer vision; two of his papers on this topic received a Best Paper award at the European Conference on Computer Vision (ECCV) in 2002. Since 2001 he has held a joint appointment with the Radiology Department at Cornell Medical School. He has also consulted extensively for a number of groups at Microsoft, including product groups as well as MSR, and has recently been serving as an expert witness for Microsoft.