Euclidean reconstruction from contour matches

This paper presents a method that recovers an Euclidean structure from contour matching results. If three or more views are available, structure reconstruction without camera calibration is possible. This is the first attempt at structure reconstruction from contour matches, though there are works on structure reconstruction from point matches. We also propose a new method that integrates more than one reconstructed 3D structure whose coordinates are represented by different camera projection matrices, so that the structures are uniformly represented by the projection matrix of the first camera. (C) 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.X112sciescopu

Euclidean Reconstruction from Contour Matches

This paper presents a method that recovers a Euclidean structure from contour matching results. If three or more views are available, structure reconstruction without camera calibration is possible. This is the first attempt at structure reconstruction from contour matches, though there are works on structure reconstruction from point matches. We also propose a new method that integrates more than one reconstructed 3D structure whose coordinates are represented by different camera projection matrices, so that the structures are uniformly represented by the projection matrix of the first camera. Key words: 3D reconstruction; Uncalibrated reconstruction; Self-calibration; Contour match 1 Introduction In projective reconstruction, the cameras need not be calibrated and reconstruction can be made directly. However the object is only reconstructed up to projective transformation. It would be desirable to make a precise reconstruction up to similarity transformations. If we assume that the i..