Bundle Adjustment for 3-D Reconstruction: Implementation and Evaluation

We describe in detail the algorithm of bundle adjustment for 3-D reconstruction from multiple images based on our latest research results. The main focus of this paper is on the handling of camera rotations and the efficiency of computation and memory usage when the number of variables is very large; an appropriate consideration of this is the core of the implementation of bundle adjustment. Computing the fundamental matrix from two views and reconstructing the 3-D structure from multiple views, we evaluate the performance of our algorithm and discuses technical issues of bundle adjustment implementation.

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

[2]  金谷 健一.  Group-theoretical methods in image understanding , 1990 .

[3]  W. Press,et al.  Numerical Recipes in Fortran: The Art of Scientific Computing.@@@Numerical Recipes in C: The Art of Scientific Computing. , 1994 .

[4]  Kenichi Kanatani,et al.  Statistical optimization for geometric computation - theory and practice , 1996, Machine intelligence and pattern recognition.

[5]  Richard I. Hartley,et al.  In Defense of the Eight-Point Algorithm , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

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

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

[8]  Richard Szeliski,et al.  Vision Algorithms: Theory and Practice , 2002, Lecture Notes in Computer Science.

[9]  Andrew Zisserman,et al.  Multiple View Geometry in Computer Vision (2nd ed) , 2003 .

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

[11]  Manolis I. A. Lourakis,et al.  Is Levenberg-Marquardt the most efficient optimization algorithm for implementing bundle adjustment? , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[12]  金谷 健一.  Statistical optimization for geometric computation : theory and practice , 2005 .

[13]  K. Kanatani,et al.  Extended FNS for Constrained Parameter Estimation , 2007 .

[14]  Kenichi Kanatani,et al.  Uncalibrated Factorization Using a Variable Symmetric Affine Camera , 2007, IEICE Trans. Inf. Syst..

[15]  Kenichi Kanatani,et al.  Fast Projective Reconstruction: Toward Ultimate Efficiency , 2008 .

[16]  Kenichi Kanatani,et al.  LATEST ALGORITHMS FOR 3-D RECONSTRUCTION FROM TWO VIEWS , 2009 .

[17]  Manolis I. A. Lourakis,et al.  SBA: A software package for generic sparse bundle adjustment , 2009, TOMS.

[18]  Kenichi Kanatani,et al.  Compact Fundamental Matrix Computation , 2009, IPSJ Trans. Comput. Vis. Appl..