Please use this identifier to cite or link to this item:
Title: Shape recognition and tracking for augmented reality
Authors: Widya Andyardja Weliamto.
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
Issue Date: 2009
Abstract: The field of 3D vision still provides many challenges in research. This thesis discusses 3D computer vision in real-time tracking and recognition for augmented reality to seamlessly merge 3D virtual objects into real image scene captured by a camera. The recognition is based on the shapes of detected objects and a set of related 2D templates. The correspondence problem is solved in a top-down recognition framework using model-based detection and tracking from 2D views. Tracking flexibility is increased for wide base line matching by using the contour shape of detected objects. The cross correlation of r-signature between the object shape and its corresponding template is performed to improve the contour detection. Subsequently, it is verified by the planar template reprojection using the homography transformation to get the 3D pose parameter. A case study is applied to alphabetic letter recognition. The angle view effect on the cross correlation value is evaluated and stabilized by using the aspect ratio normalization.
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Theses

Files in This Item:
File Description SizeFormat 
  Restricted Access
7.6 MBAdobe PDFView/Open

Page view(s) 50

Updated on Nov 25, 2020

Download(s) 50

Updated on Nov 25, 2020

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.