Automatic camera recovery for closed or open image sequences
We describe progress in completely automatically recovering 3D scene structure together with 3D camera positions from a sequence of images acquired by an unknown camera undergoing unknown movement.
The main departure from previous structure from motion strategies is that processing is not sequential. Instead a hierarchical approach is employed building from image triplets and associated trifocal tensors. This is advantageous both in obtaining correspondences and also in optimally distributing error over the sequence.
The major step forward is that closed sequences can now be dealt with easily. That is, sequences where part of a scene is revisited at a later stage in the sequence. Such sequences contain additional constraints, compared to open sequences, from which the reconstruction can now benefit.
The computed cameras and structure are the backbone of a system to build texture mapped graphical models directly from image sequences.
KeywordsProjection Matrice Bundle Adjustment Closed Sequence Reprojection Error Trifocal Tensor
Unable to display preview. Download preview PDF.
- 1.N. Ayache. Artificial vision for mobile robots. MIT Press, Cambridge, 1991.Google Scholar
- 2.P. Beardsley, P. Torr, and A. Zisserman. 3D model acquisition from extended image sequences. In Proc. ECCV, LNCS 1064/1065, pages 683–695. Springer-Verlag, 1996.Google Scholar
- 3.P. Beardsley, A. Zisserman, and D. W. Murray. Navigation using affine structure and motion. In Proc. ECCV, LNCS 800/801, pages 85–96. Springer-Verlag, 1994.Google Scholar
- 4.C. J. Harris. Determination of ego-motion from matched points. In Alvey Vision Conf., pages 189–192, 1987.Google Scholar
- 5.C. J. Harris and M. Stephens. A combined corner and edge detector. In Alvey Vision Conf., pages 147–151, 1988.Google Scholar
- 6.R. I. Hartley. Euclidean reconstruction from uncalibrated views. In J. Mundy, A. Zisserman, and D. Forsyth, editors, Applications of Invariance in Computer Vision, LNCS 825, pages 237–256. Springer-Verlag, 1994.Google Scholar
- 7.R. I. Hartley. A linear method for reconstruction from lines and points. In Proc. ICCV, pages 882–887, 1995.Google Scholar
- 8.R. I. Hartley and P. Sturm. Triangulation. In American Image Understanding Workshop, pages 957–966, 1994.Google Scholar
- 9.A. Heyden and K. åström. Euclidean reconstruction from image sequences with varying and unknown focal length and principal point. In Proc. CVPR, 1997.Google Scholar
- 10.D. Jacobs. Linear fitting with missing data: Applications to structure from motion and to characterizing intensity images. In Proc. CVPR, pages 206–212, 1997.Google Scholar
- 11.S. Laveau. Géométrie d'un système de N caméras. Théorie, estimation et applications. PhD thesis, INRIA, 1996.Google Scholar
- 12.S. J. Maybank and A. Shashua. Ambiguity in reconstruction from images of six points. In Proc. ICCV, pages 703–708, 1998.Google Scholar
- 13.P. F. McLauchlan and D. W. Murray. A unifying framework for structure from motion recovery from image sequences. In Proc. ICCV, pages 314–320, 1995.Google Scholar
- 14.P. F. McLauchlan, I. D. Reid, and D. W. Murray. Recursive affine structure and motion from image sequences. In Proc. ECCV, volume 1, pages 217–224, May 1994.Google Scholar
- 15.R. Mohr, B. Boufama, and P. Brand. Accurate projective reconstruction. In J. Mundy, A. Zisserman, and D. Forsyth, editors, Applications of Invariance in Computer Vision, LNCS 825. Springer-Verlag, 1994.Google Scholar
- 16.M. Pollefeys, R. Koch, and L. Van Gool. Self calibration and metric reconstruction in spite of varying and unknown internal camera parameters. In Proc. ICCV, pages 90–96, 1998.Google Scholar
- 17.J. Porrill. Optimal combination and constraints for geometrical sensor data. Intl. J. of Robotics Research, 7(6):66–77, 1988.Google Scholar
- 19.C. Schmid and A. Zisserman. Automatic line matching across views. In Proc. CVPR, pages 666–671, 1997.Google Scholar
- 21.H. Y. Shum, M. Hebert, K. Ikeuchi, and R. Reddy. An integral approach to free-form object modeling. In Proc. ICCV, pages 870–875, 1995.Google Scholar
- 22.G. Sparr. Simultaneous reconstruction of scene structure and camera locations from uncalibrated image sequences. In Proc. ICPR, 1996.Google Scholar
- 24.P. Sturm. Vision 3D non calibrée: Contributions à la reconstruction projective et étude des mouvements critiques pour l'auto calibrage. PhD thesis, INRIA RhÔne-Alpes, 1997.Google Scholar
- 25.P. Sturm and W. Triggs. A factorization based algorithm for multi-image projective structure and motion. In Proc. ECCV, pages 709–720, 1996.Google Scholar
- 27.P. H. S. Torr, A. W. Fitzgibbon, and A. Zisserman. Maintaining multiple motion model hypotheses over many views to recover matching and structure. In Proc. ICCV, pages 485–491, January 1998.Google Scholar
- 31.W. Triggs. Auto-calibration and the absolute quadric. In Proc. CVPR, pages 609–614, 1997.Google Scholar
- 33.Z. Zhang and O. Faugeras. 3D Dynamic Scene Analysis. Springer-Verlag, 1992.Google Scholar
- 34.A. Zisserman, P. Beardsley, and I. Reid. Metric calibration of a stereo rig. In IEEE Workshop on Representation of Visual Scenes, Boston, pages 93–100, 1995.Google Scholar