Learning Models for Multi-Viewpoint Object Detection

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.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Kushal, Akash M.

Contributors dc:contributor

• Ponce, Jean

• Engineering, Robotics

Language dc:language

eng

Identifier

(MiAaPQ)AAI3337833

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/81832