A Practical Approach for 3D Building Modeling from Uncalibrated Video Sequences

This paper presents an approach for reconstructing a realistic 3D model of a building from its uncalibrated video sequences taken by a hand-held camera. The novelty of this approach lies in the integration of some prior scene knowledge in the different stages of the Structure From Motion problem (SFM). First, the coplanarity of buildings is considered in the calculation of the fundamental matrices to deal with the critical configurations. Second, the line parallelism and plane orthogonality are transformed to the constraints on the absolute quadric during camera auto-calibration. This makes some critical cases solvable and the reconstruction more Euclidean. The approach is implemented and validated using simulated data and real image data. The experimental results at the end of the paper show the effectiveness of our approach.

[1]  Anders Heyden,et al.  Flexible calibration: minimal cases for auto-calibration , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[2]  Luc Van Gool,et al.  Self-Calibration from the Absolute Conic on the Plane at Infinity , 1997, CAIP.

[3]  Andrew Zisserman,et al.  Robust Detection of Degenerate Configurations while Estimating the Fundamental Matrix , 1998, Comput. Vis. Image Underst..

[4]  Reinhard Koch,et al.  Self-Calibration and Metric Reconstruction Inspite of Varying and Unknown Intrinsic Camera Parameters , 1999, International Journal of Computer Vision.

[5]  Richard I. Hartley,et al.  Euclidean Reconstruction from Uncalibrated Views , 1993, Applications of Invariance in Computer Vision.

[6]  Fredrik Kahl.  Critical motions and ambiguous Euclidean reconstructions in auto-calibration , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[7]  Philip H. S. Torr,et al.  Outlier detection and motion segmentation , 1993, Other Conferences.

[8]  Reinhard Koch,et al.  Self-calibration and metric reconstruction in spite of varying and unknown internal camera parameters , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[9]  Rachid Deriche,et al.  A Robust Technique for Matching two Uncalibrated Images Through the Recovery of the Unknown Epipolar Geometry , 1995, Artif. Intell..

[10]  A. Heyden,et al.  Euclidean reconstruction from constant intrinsic parameters , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[11]  Andrew Zisserman,et al.  Applications of Invariance in Computer Vision , 1993, Lecture Notes in Computer Science.

[12]  Peter F. Sturm,et al.  Critical motion sequences for monocular self-calibration and uncalibrated Euclidean reconstruction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[13]  O. D. Faugeras,et al.  Camera Self-Calibration: Theory and Experiments , 1992, ECCV.