Semi-automatic metric reconstruction of buildings from self-calibration: preliminary results on the evaluation of a linear camera self-calibration method
Huynh, D.Q., Chou, Y.S. and Tsui, H.T. (2000) Semi-automatic metric reconstruction of buildings from self-calibration: preliminary results on the evaluation of a linear camera self-calibration method. In: 15th international Conference on Pattern Recognition, 3 - 7 September, Barcelona , Spain.
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In this paper, we investigate the linear self-calibration method proposed by Newsam et al  for our project on 3D reconstruction of architectural buildings. Tins self-calibration method assumes that the principal point is known, the camera has square pixels and has no skew. It allows 3D shape to be reconstructed from two images while giving the camera the freedom to vary its focal length. Since the paper by Newsam et al reports only the theoretical work on camera self-calibration, in this paper, we evaluate the focal lengths obtained from their method with both synthetic data and real data. In real data where known 3D data are available, Tsai's calibration method is used for comparison. Our experimental results show that the focal lengths from the two methods differed by less than 5% and the reconstructed 3D shape was very good in that angles were well preserved. Future research will focus on improvement of 3D reconstruction in the presence of small image noise and further develop this method into a package for 3D reconstruction of buildings to be used by a layperson.
|Publication Type:||Conference Paper|
|Murdoch Affiliation:||School of Information Technology|
|Copyright:||© 2000 IEEE|
|Notes:||Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This paper appears in: Proceedings of the 15th International Conference on Pattern Recognition, 2000, Barcelona , Spain, pp 599-602.|
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