אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

In the generalized projection-based M-estimator (gpbM), published a few years ago, multiple structures with different scales were estimated without the scale parameter specified for each inlier structure. However, the gpbM can be defined from much simpler assumptions. From M trials based on the elemental subsets, we find a small group of the data points which produces the minimum sum of the Mahalanobis distances, and expand it to obtain the scale of a structure. This value is used in the mean shift to recover the structure itself. The iterative process returns the result in a list sorted by strength, where the inlier structures are always the strongest ones at the beginning. Several synthetic and real examples are presented to illustrate every aspect of this algorithm. Joint work with Xiang Yang Dept. of Mechanical and Aerospace Engineering, Rutgers University.

Bio:
Peter Meer received the Dipl. Eng. degree from the Bucharest Polytechnic Institute, Romania in 1971, and D.Sc. from the Technion In 1986, both in electrical engineering .In 1991 he joined the Department of Electrical and Computer Engineering, Rutgers University, and is currently a Professor. He has held visiting appointments in Japan, Korea, Sweden, Israel and France, He was an Associate Editor of the IEEE Transaction on Pattern Analysis and Machine Intelligence between 1998 and 2002, was a Guest Editor of Computer Vision and Image Understanding for a special issue on robustness in computer vision in 2000, and was a member of the Editorial Board of Pattern Recognition between 1989 and 2005. With coauthors Dorin Comaniciu and Visvanathan Ramesh he received at the 2010 CVPR the Longuet-Higgins prize for fundamental contributions in computer vision in the past ten years. His research interest is in application of modern statistical methods to image understanding problems. He is an IEEE Fellow.