Graphical Models for Computer Vision

author: Pedro Felzenszwalb, Computer Science Department, Brown University
recorded by: UAI2012 student volunteers
published: Sept. 17, 2012,   recorded: August 2012,   views: 767

Slides

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Delicious Bibliography

Description

Graphical models provide a powerful framework for expressing and solving a variety of inference problems. The approach has had an enormous impact in computer vision. In this talk I will review some of the developments that have enabled this impact, focusing on efficient algorithms that exploit the structure of vision problems. I will discuss several applications including the low-level vision problem of image restoration, the mid-level problem of segmentation and the high-level problem of model-based recognition. I will also discuss some of the current challenges in the area.

See Also:

Download slides icon Download slides: uai2012_felzenszwalb_computer_vision_01.pdf (3.3┬áMB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: