Graduate Thesis Or Dissertation

 

Region based image matching for 3D object recognition Public Deposited

Downloadable Content

Download PDF
https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/x059cc634

Descriptions

Attribute NameValues
Creator
Abstract
  • 3D object recognition is a very difficult and important problem in computer vision, arising in a wide range of applications. Typically in 3D object recognition, interest points are extracted from images and then matched. A shortcoming of this approach is that points only carry local visual information. Therefore, there could be many similar interest points, and these similar points could confuse the matching algorithm. In this thesis, we focus on region-based image matching for 3D object recognition. The main steps that we take are: 1) Extract regions from the image segmentations 2) Represent the objects with the aspect graph of regions 3) Match the given images based on region properties and special layout of regions. Our experiments on a challenging dataset show that we are able to match regions of the objects under 3D transforms. Our main contribution is that while traditional approaches concentrate on matching points, we focus on matching regions of objects. We are the first to show that matching segments of these challenging images is possible under 3D transforms.
Resource Type
Date Available
Date Copyright
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Academic Affiliation
Non-Academic Affiliation
Keyword
Subject
Rights Statement
Language
Replaces
Additional Information
  • description.provenance : Rejected by Laura Wilson(laura.wilson@oregonstate.edu), reason: extra page at end of document on 2010-07-16T23:22:38Z (GMT)
  • description.provenance : Approved for entry into archive by Julie Kurtz(julie.kurtz@oregonstate.edu) on 2010-06-09T15:44:12Z (GMT) No. of bitstreams: 1 LiuTian2010.pdf: 4206624 bytes, checksum: 8c1bb91c751f6aac5070a0600d11ed06 (MD5)
  • description.provenance : Submitted by Tian Liu (liuti@onid.orst.edu) on 2010-07-19T07:47:18Z No. of bitstreams: 1 LiuTian2010.pdf: 4206163 bytes, checksum: 678cb166626dd55cf1d23dab237d2f3f (MD5)
  • description.provenance : Approved for entry into archive by Julie Kurtz(julie.kurtz@oregonstate.edu) on 2010-07-19T15:50:55Z (GMT) No. of bitstreams: 1 LiuTian2010.pdf: 4206163 bytes, checksum: 678cb166626dd55cf1d23dab237d2f3f (MD5)
  • description.provenance : Made available in DSpace on 2010-07-19T18:00:01Z (GMT). No. of bitstreams: 1 LiuTian2010.pdf: 4206163 bytes, checksum: 678cb166626dd55cf1d23dab237d2f3f (MD5)
  • description.provenance : Approved for entry into archive by Laura Wilson(laura.wilson@oregonstate.edu) on 2010-07-19T18:00:01Z (GMT) No. of bitstreams: 1 LiuTian2010.pdf: 4206163 bytes, checksum: 678cb166626dd55cf1d23dab237d2f3f (MD5)
  • description.provenance : Submitted by Tian Liu (liuti@onid.orst.edu) on 2010-06-09T06:09:18Z No. of bitstreams: 1 LiuTian2010.pdf: 4206624 bytes, checksum: 8c1bb91c751f6aac5070a0600d11ed06 (MD5)

Relationships

Parents:

This work has no parents.

Items