Automatic scene structure and camera motion using a catadioptric system

Fully automatic methods are presented for the estimation of scene structure and camera motion from an image sequence acquired by a catadioptric system. The first contribution is the design of bundle adjustments for both central and non-central models, by taking care of the smoothness of the minimized error functions. The second contribution is an extensive experimental study for long sequences of catadioptric images in a context useful for applications: a hand-held and equiangular camera moving on the ground. An equiangular camera is non-central and provides uniform resolution in the image radial direction. Many experiments dealing with robustness, accuracy, uncertainty, comparisons between both central and non-central models, and piecewise planar 3D modeling are provided.

[1]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[2]  Gregory D. Hager,et al.  Fast and Globally Convergent Pose Estimation from Video Images , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Tomás Svoboda,et al.  Matching in Catadioptric Images with Appropriate Windows, and Outliers Removal , 2001, CAIP.

[4]  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).

[5]  Kostas Daniilidis,et al.  Structure and motion from uncalibrated catadioptric views , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[6]  Zhanyi Hu,et al.  Camera Calibration from the Quasi-affine Invariance of Two Parallel Circles , 2004, ECCV.

[7]  Richard Szeliski,et al.  3-D Scene Data Recovery Using Omnidirectional Multibaseline Stereo , 2004, International Journal of Computer Vision.

[8]  Sing Bing Kang,et al.  Catadioptric self-calibration , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[9]  James R. Bergen,et al.  Visual odometry , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[10]  Andrew Zisserman,et al.  Multiple view geometry in computer visiond , 2001 .

[11]  Tomás Pajdla,et al.  Structure from motion with wide circular field of view cameras , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Shree K. Nayar,et al.  A general imaging model and a method for finding its parameters , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[13]  Gilad Adiv,et al.  Inherent Ambiguities in Recovering 3-D Motion and Structure from a Noisy Flow Field , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Long Quan,et al.  A quasi-dense approach to surface reconstruction from uncalibrated images , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  O. Faugeras,et al.  The Geometry of Multiple Images , 1999 .

[16]  Konrad Schindler,et al.  On Robust Regression in Photogrammetric Point Clouds , 2003, DAGM-Symposium.

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

[18]  Jiri Matas,et al.  Robust wide-baseline stereo from maximally stable extremal regions , 2004, Image Vis. Comput..

[19]  William H. Press,et al.  Numerical recipes in C , 2002 .

[20]  Andrew W. Fitzgibbon,et al.  Bundle Adjustment - A Modern Synthesis , 1999, Workshop on Vision Algorithms.

[21]  Kaj Madsen,et al.  Methods for Non-Linear Least Squares Problems (2nd ed.) , 2004 .

[22]  S. Bougnoux,et al.  From projective to Euclidean space under any practical situation, a criticism of self-calibration , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[23]  Kostas Daniilidis,et al.  A Unifying Theory for Central Panoramic Systems and Practical Applications , 2000, ECCV.

[24]  Maxime Lhuillier,et al.  Automatic Structure and Motion using a Catadioptric Camera , 2005 .

[25]  S. P. Mudur,et al.  Three-dimensional computer vision: a geometric viewpoint , 1993 .

[26]  Kaj Madsen,et al.  Methods for Non-Linear Least Squares Problems , 1999 .

[27]  Daniel G. Aliaga Accurate Catadioptric Calibration for Real-time Pose Estimation of Room-size Environments , 2001, ICCV.

[28]  Long Quan,et al.  Match Propagation for Image-Based Modeling and Rendering , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[29]  Olivier D. Faugeras,et al.  The geometry of multiple images - the laws that govern the formation of multiple images of a scene and some of their applications , 2001 .

[30]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.