6.881 Representation and Modeling for Image Analysis (H)

L MW1-2:30
Professor Polina Golland, polina@csail.mit.edu
Prereq.: 6.432 or 6.866 or 6.867 or permission of instructor
3-0-9

This subject qualifies as an Artificial Intelligence Engineering concentration subject.

Most algorithms in computer vision and image analysis consist of two important components: representation and modeling/estimation algorithm. Representation defines what is important about the objects. The modeling techniques extract the information from images to instantiate the representation for the particular objects present in the scene. In this seminar, we will discuss popular representations (contours, level sets, deformation fields, etc.) and useful methods that allow us to extract and manipulate image information (including manifold fitting, markov random fields, expectation maximization, clustering and others).

For each concept (a new representation or an estimation algorithm), an introductory lecture on the mathematical foundations of the concept will be followed by a discussion of two or three research papers that employ the concept in computer vision, medical and biological imaging. We will aim to understand the fundamental techniques and to recognize situations in which these techniques promise to improve the quality of the analysis.