Computer vision

author: Richard Hartley, Australian National University
published: April 1, 2009,   recorded: February 2009,   views: 35988

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A pseudo-boolean function is a function from the space B^n of boolean (0-1) vector to the real numbers. They occur naturally in problems in computer vision related to segmentation where every pixel in an image should be labelled 0 or 1 to minimize a certain cost function. Although the minimization of such functions in in general NP hard, many techniques have been develloped to minimize certain classes of such functions. This is the topic of pseudo-boolean optimization, which will be the subject of this talk. Useful methods include graph-cuts algorithms, message passing and linear programming relaxation. The extension to functions with a finite label set will also be considered.

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Reviews and comments:

Comment1 pifono, June 21, 2010 at 11:22 p.m.:

Poor speaker... Apparently far to be a master on the discussed topic!

Comment2 glowsky, June 27, 2010 at 8:51 p.m.:

This guy should get retired ASAP. At this point he brings no value by his poor explanations. Definitively not a skilled lecturer.

Comment3 Ray Phan, January 24, 2011 at 1:58 a.m.:

I don't know what you guys are talking about. I think he's a great lecturer. You have to have some knowledge on how MRFs and Graph Cuts work before hand, but nevertheless, the guy is great.

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