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Title:Learning Models for Multi-Viewpoint Object Detection
Author(s):Kushal Akash M.
Doctoral Committee Chair(s):Ponce, Jean
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Engineering, Robotics
Abstract:We also propose two different approaches for modeling the inter-part relations and algorithms for efficiently learning the model parameters. The first approach uses a generative model that models the joint probability distribution over the locations and visibility of all the object parts. The second approach employs a discriminative Conditional Random Field based model to encode the relative geometry and co-occurrence constraints.
Issue Date:2008
Type:Text
Language:English
Description:135 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008.
URI:http://hdl.handle.net/2142/81832
Other Identifier(s):(MiAaPQ)AAI3337833
Date Available in IDEALS:2015-09-25
Date Deposited:2008


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