Structure from Motion Estimation with Positional Cues

We present a system for structure from motion estimation using additional positioning data such as GPS data. The system incorporates the additional data in the outlier detection, the initial estimates and the final bundle adjustment. The initial solution is based on a novel objective function which is solved using convex optimization. This objective function is also used for outlier detection and removal. The initial solution is then refined based on a novel near L 2 minimization of the reprojection error using convex optimization methods. We present results on synthetic and real data, that shows the robustness, accuracy and speed of the proposed method.

[1]  Shree K. Nayar,et al.  Computer Vision - ACCV 2006, 7th Asian Conference on Computer Vision, Hyderabad, India, January 13-16, 2006, Proceedings, Part I , 2006, ACCV.

[2]  Richard I. Hartley,et al.  L-8Minimization in Geometric Reconstruction Problems , 2004, CVPR.

[3]  Takeo Kanade,et al.  Quasiconvex Optimization for Robust Geometric Reconstruction , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Keiichi Uchimura,et al.  Fusion of vision, 3D gyro and GPS for camera dynamic registration , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[5]  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..

[6]  Jochen Trumpf,et al.  L1 rotation averaging using the Weiszfeld algorithm , 2011, CVPR 2011.

[7]  Thomas Deselaers,et al.  ClassCut for Unsupervised Class Segmentation , 2010, ECCV.

[8]  Marc Pollefeys,et al.  Disambiguating visual relations using loop constraints , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  Richard I. Hartley,et al.  Removing Outliers Using The L\infty Norm , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[10]  Pascal Fua,et al.  Dynamic and scalable large scale image reconstruction , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[11]  Andrew Owens,et al.  Discrete-continuous optimization for large-scale structure from motion , 2011, CVPR 2011.

[12]  Michel Dhome,et al.  Towards geographical referencing of monocular SLAM reconstruction using 3D city models: Application to real-time accurate vision-based localization , 2009, CVPR.

[13]  A. Bartoli,et al.  Bi-Objective Bundle Adjustment With Application to Multi-Sensor SLAM , 2010 .

[14]  Arnak S. Dalalyan,et al.  L1-Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview Geometry , 2009, NIPS.

[15]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[16]  Richard Szeliski,et al.  Building Rome in a day , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[17]  Sanjiv Singh,et al.  Motion Estimation from Image and Inertial Measurements , 2004, Int. J. Robotics Res..

[18]  Venu Madhav Govindu,et al.  Robustness in Motion Averaging , 2006, ACCV.

[19]  Kurt Konolige,et al.  Large-Scale Visual Odometry for Rough Terrain , 2007, ISRR.

[20]  Marc Pollefeys,et al.  Practical Methods for Convex Multi-view Reconstruction , 2010, ECCV.

[21]  Maxime Lhuillier Fusion of GPS and structure-from-motion using constrained bundle adjustments , 2011, CVPR 2011.

[22]  Vincent Lepetit,et al.  Revisiting the PnP Problem with a GPS , 2009, ISVC.

[23]  A. C. Aitken IV.—On Least Squares and Linear Combination of Observations , 1936 .

[24]  Kristy Sim,et al.  Removing outliers using the L∞ Norm , 2006, CVPR 2006.

[25]  F. Kahl Multiple View Geometry and the -norm , 2005 .

[26]  Fredrik Kahl,et al.  Multiple view geometry and the L/sub /spl infin//-norm , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[27]  Tomás Pajdla,et al.  Robust Rotation and Translation Estimation in Multiview Reconstruction , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.