TOWARDS STRUCTURELESS BUNDLE ADJUSTMENT WITH TWO- AND THREE-VIEW STRUCTURE APPROXIMATION

Abstract. The global approaches solve SfM problems by independently inferring relative motions, followed be a sequential estimation of global rotations and translations. It is a fast approach but not optimal because it relies only on pairs and triplets of images and it is not a joint optimisation. In this publication we present a methodology that increases the quality of global solutions without the usual computational burden tied to the bundle adjustment. We propose an efficient structure approximation approach that relies on relative motions known upfront. Using the approximated structure, we are capable of refining the initial poses at very low computational cost. Compared to different benchmark datasets and software solutions, our approach improves the processing times while maintaining good accuracy.

[1]  Jan-Michael Frahm,et al.  Structure-from-Motion Revisited , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

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

[3]  Pascal Monasse,et al.  A Critical Review of the Trifocal Tensor Estimation , 2017, PSIVT.

[4]  Hongdong Li,et al.  Rotation Averaging , 2013, International Journal of Computer Vision.

[5]  Ping Tan,et al.  A Global Linear Method for Camera Pose Registration , 2013, 2013 IEEE International Conference on Computer Vision.

[6]  Dieter Schmalstieg,et al.  Robust Incremental Structure from Motion , 2010 .

[7]  Takeo Kanade,et al.  Shape and motion from image streams under orthography: a factorization method , 1992, International Journal of Computer Vision.

[8]  Andrea Fusiello,et al.  Hierarchical structure-and-motion recovery from uncalibrated images , 2015, Comput. Vis. Image Underst..

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

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

[11]  Helmut Mayer Efficient Hierarchical Triplet Merging for Camera Pose Estimation , 2014, GCPR.

[12]  Richard Szeliski,et al.  Bundle Adjustment in the Large , 2010, ECCV.

[13]  Peter F. Sturm,et al.  Exploiting Loops in the Graph of Trifocal Tensors for Calibrating a Network of Cameras , 2010, ECCV.

[14]  Tobias Höllerer,et al.  Optimizing the Viewing Graph for Structure-from-Motion , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[15]  Steven M. Seitz,et al.  Photo tourism: exploring photo collections in 3D , 2006, ACM Trans. Graph..

[16]  Carl Olsson,et al.  Non-sequential structure from motion , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[17]  Dieter Fritsch,et al.  STRUCTURELESS BUNDLE ADJUSTMENT WITH SELF-CALIBRATION USING ACCUMULATED CONSTRAINTS , 2016 .

[18]  Sameer Agarwal,et al.  Visibility Based Preconditioning for bundle adjustment , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

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

[20]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

[21]  Olivier Faugeras,et al.  Motion and Structure from Motion in a piecewise Planar Environment , 1988, Int. J. Pattern Recognit. Artif. Intell..

[22]  Noah Snavely,et al.  Robust Global Translations with 1DSfM , 2014, ECCV.

[23]  Pascal Monasse,et al.  OpenMVG: Open Multiple View Geometry , 2016, RRPR@ICPR.

[24]  Frank Dellaert,et al.  Incremental Light Bundle Adjustment , 2012, BMVC.

[25]  Lei Zhou,et al.  Very Large-Scale Global SfM by Distributed Motion Averaging , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[26]  Pascal Fua,et al.  On benchmarking camera calibration and multi-view stereo for high resolution imagery , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[27]  R. Hartley,et al.  Multiple-View Geometry under the L 1-Norm , 2007 .

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

[29]  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).

[30]  Alberto Ruiz,et al.  GEA optimization for live structureless motion estimation , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[31]  Venu Madhav Govindu,et al.  Combining two-view constraints for motion estimation , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

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

[33]  Matthijs C. Dorst Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[34]  Long Quan,et al.  Parallel Structure from Motion from Local Increment to Global Averaging , 2017 .

[35]  Jan-Michael Frahm,et al.  Relative Bundle Adjustment Based on Trifocal Constraints , 2010, ECCV Workshops.

[36]  Anders P. Eriksson,et al.  Outlier removal using duality , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[37]  E. Rupnik,et al.  MicMac – a free, open-source solution for photogrammetry , 2017, Open Geospatial Data, Software and Standards.

[38]  Pascal Monasse,et al.  Global Fusion of Relative Motions for Robust, Accurate and Scalable Structure from Motion , 2013, ICCV.

[39]  Richard Szeliski,et al.  Pushing the Envelope of Modern Methods for Bundle Adjustment , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[40]  Ira Kemelmacher-Shlizerman,et al.  Global Motion Estimation from Point Matches , 2012, 2012 Second International Conference on 3D Imaging, Modeling, Processing, Visualization & Transmission.

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

[42]  M. Pierrot Deseilligny,et al.  APERO, AN OPEN SOURCE BUNDLE ADJUSMENT SOFTWARE FOR AUTOMATIC CALIBRATION AND ORIENTATION OF SET OF IMAGES , 2012 .

[43]  A. Iserles Numerical recipes in C—the art of scientific computing , by W. H. Press, B. P. Flannery, S. A. Teukolsky and W. T. Vetterling. Pp 735. £27·50. 1988. ISBN 0-521-35465-X (Cambridge University Press) , 1989, The Mathematical Gazette.