loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
15th International Conference on Pattern Recognition (ICPR'00) - Volume 1
Single View Computer Vision in Polyhedral World: Geometric Inference and Performance Characterization
Barcelona, Spain
September 03-September 08
ISBN: 0-7695-0750-6
Mingzhou Song, University of Washington
Aiwen Guo, University of Washington
Robert M. Haralick, University of Washington
An algorithm for making consistent 2-D to 3-D geometric inference in polyhedral world using one perspective line drawing is described. Hypotheses are made on the internal angles of visible faces. The normals to the face planes are then determined. Valid normals lead to the reconstruction of the 3-D polyhedral world up to a scale factor. The performance of the algorithm is verified by using covariance matrix propagation. The experimental results show satisfactory performance. The general propagation formulae for the covariance matrix of both observed and inferred quantities are also derived.
Citation:
Mingzhou Song, Aiwen Guo, Robert M. Haralick, "Single View Computer Vision in Polyhedral World: Geometric Inference and Performance Characterization," icpr, vol. 1, pp.1766, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 1, 2000
Usage of this product signifies your acceptance of the Terms of Use.