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Course Info

  • Course Number / Code:
  • 6.881 (Spring 2005) 
  • Course Title:
  • Representation and Modeling for Image Analysis 
  • Course Level:
  • Graduate 
  • Offered by :
  • Massachusetts Institute of Technology (MIT)
    Massachusetts, United States  
  • Department:
  • Electrical Engineering and Computer Science 
  • Course Instructor(s):
  • Prof. Polina Golland 
  • Course Introduction:

  • 6.881 Representation and Modeling for Image Analysis

    Spring 2005

    Course Highlights

    This course features lecture notes for a number of sessions. In addition an extensive bibliography of assigned and recommended readings is provided in the readings section. Extensive project information, including student submissions, are also provided in the projects section.

    Course Description

    Most algorithms in computer vision and image analysis can be understood in terms of two important components: a representation and a modeling/estimation algorithm. The representation defines what information is important about the objects and is used to describe them. 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 (such as contours, level sets, deformation fields) 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 -- a lecture on the mathematical foundations of the concept will be followed by a discussion of two or three relevant research papers in computer vision, medical and biological imaging, that use the concept in different ways. We will aim to understand the fundamental techniques and to recognize situations in which these techniques promise to improve the quality of the analysis.

    Technical Requirements

    Postscript viewer software, such as Ghostscript/Ghostview, can be used to view the .ps files found on this course site.


This course content is a redistribution of MIT Open Courses. Access to the course materials is free to all users.

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