Object categorization using collections of parts and second order pooling features
Sukumar, Pritam
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https://hdl.handle.net/2142/45296
Description
Title
Object categorization using collections of parts and second order pooling features
Author(s)
Sukumar, Pritam
Issue Date
2013-08-22T16:35:12Z
Director of Research (if dissertation) or Advisor (if thesis)
Hoiem, Derek W.
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
computer vision
machine learning
object categorization
Abstract
This thesis presents an investigation of the Collection of Parts Model for object categorization. Multiclass categorization is performed using the Collections of Parts model. Results using Support Vector Machines, L1 Logistic Regression and Boosted Decision Trees are presented and discussed. Methods to analyze confusion in these results are developed and results are presented. The Collections of Parts model is augmented with features from features generated by Second Order Pooling resulting in a significant improvement in performance.
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