Speaker |
Vladimir Krylov |
|---|---|
Affiliation |
UCL |
Date |
Friday, 22 March 2013 |
Time |
12:30-14:00 |
Location |
Zoom |
Link |
Cruciform B404 - LT2 |
Event series |
DeepMind/ELLIS CSML Seminar Series |
Abstract |
Numerous image processing applications require automatic extraction of geometrical structure information: from lines in mammographic images (for cancer detection) to buildings and roads on satellite imagery (for coregistration and mapping). In this talk I am going to present several applications of conventional Markov Chain Monte Carlo (MCMC) and reversible jump MCMC to extraction of such geometrical structure from 2D images. More specifically, each of the extracted objects is modeled by a geometrical element (e.g., line segments, rectangles, circles, ellipses) whose location and parameters are adjusted throughout iterative MCMC process in order to accurately fit the data. Dr. Vladimir Krylov is a Research Associate working with Dr. James Nelson in the Department of Statistical Science at UCL. His research interests are statistical image and signal processing, in particular pattern recognition in medical and remotely sensed imagery. Slides for the talk: PDF |
Biography |