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Title:Scene Discovery by Matrix Factorization
Author(s):Loeff, Nicolas; Farhadi, Ali; Forsyth, David A.
Subject(s):computer animation
computer graphics
Abstract:What constitutes a scene? Defining a meaningful vocabulary for scene discovery is a challenging problem that has important consequences for object recognition. We consider scenes to depict correlated objects and present visual similarity. We introduce a max-margin factorization model that finds a low dimensional sub-space with high discriminative power for correlated annotations. We postulate this space should allow us to discover a large number of scenes in unsupervised data; we show scene discrimination results on par with supervised approaches. This model also produces state of the art word prediction results including good annotation completion.
Issue Date:2008-01
Genre:Technical Report
Type:Text
URI:http://hdl.handle.net/2142/11420
Other Identifier(s):UIUCDCS-R-2008-2928
Rights Information:You are granted permission for the non-commercial reproduction, distribution, display, and performance of this technical report in any format, BUT this permission is only for a period of 45 (forty-five) days from the most recent time that you verified that this technical report is still available from the University of Illinois at Urbana-Champaign Computer Science Department under terms that include this permission. All other rights are reserved by the author(s).
Date Available in IDEALS:2009-04-22


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