| Title | Euclidean Reconstruction from Image Sequences with Varying and Unknown Focal Length and Principal Point |
| Authors | Anders Heyden, Karl Åström |
| Alternative Location | http://dx.doi.org/10.1109/C... |
| Publication | Proceedings Conference on Computer Vision and Pattern Recognition |
| Year | 1997 |
| Pages | 438 - 443 |
| Document type | Conference paper |
| Conference name | Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
| Conference Date | 1997-06-17 - 19 |
| Conference Location | San Juan, Puerto Rico |
| Status | Published |
| Language | eng |
| Publisher | IEEE Comput. Soc |
| Abstract English | The special case of reconstruction from image sequences taken by cameras with skew equal to 0 and aspect ratio equal to 1 has been treated. These type of cameras, here called cameras with Euclidean image planes, represent rigid projections where neither the principal point nor the focal length is known, it is shown that it is possible to reconstruct an unknown object from images taken by a camera with Euclidean image plane up to similarity transformations, i.e., Euclidean transformations plus changes in the global scale. An algorithm, using bundle adjustment techniques, has been implemented. The performance of the algorithm is shown on simulated data |
| Keywords | cameras, unknown principal point, varying principal point, unknown focal length, image sequences, varying focal length, Euclidean reconstruction, skew, aspect ratio, Euclidean image planes, rigid projections, unknown object reconstruction, similarity transformations, Euclidean transformations, global scale, algorithm performance, bundle adjustment techniques, simulated data, image reconstruction, |
| ISBN/ISSN/Other | ISBN: 0 8186 7822 4 |
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