lec14_reco1 - CS6670: Computer Vision Noah Snavely Lecture...

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Lecture 14: Introduction to Recognition CS6670: Computer Vision Noah Snavely mountain building tree banner vendor people street lamp
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Announcements Final project page up, at http://www.cs.cornell.edu/courses/cs6670/2009fa/projects/p4/ One person from each team should submit a proposal (to CMS) by next Wednesday at 11:59pm Project 3: eigenfaces will be posted on the web soon Adarsh will capture photos at the end of class project will include a challenge competition
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What do we mean by ―object recognition‖? Next 15 slides adapted from Li, Fergus, & Torralba’s excellent short course on category and object recognition
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Verification: is that a lamp?
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Detection: are there people?
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Identification: is that Potala Palace?
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Object categorization mountain building tree banner vendor people street lamp
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Scene and context categorization outdoor city
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Object recognition Is it really so hard? This is a chair Find the chair in this image Output of normalized correlation
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Object recognition Is it really so hard? Find the chair in this image Pretty much garbage Simple template matching is not going to make it
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Object recognition Is it really so hard? Find the chair in this image A “popular method is that of template matching, by point to point correlation of a model pattern with the image pattern. These techniques are inadequate for three-dimensional scene analysis for many reasons, such as occlusion, changes in viewing angle, and articulation of parts.” Nivatia & Binford, 1977.
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Brady, M. J., & Kersten, D. (2003). Bootstrapped learning of novel objects. J Vis, 3(6), 413-422 And it can get a lot harder
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Applications: Computational photography
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Applications: Assisted driving meters
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This note was uploaded on 09/27/2010 for the course CS 667 at Cornell University (Engineering School).

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lec14_reco1 - CS6670: Computer Vision Noah Snavely Lecture...

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