Single View Computer Vision in Polyhedral
World:
Mingzhou
Song, Aiwen Guo and Robert M. Haralick
Abstract
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 input and output variables are also derived.