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An iterative method based on 1D subspace for projective reconstruction

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Języki publikacji
EN
Abstrakty
EN
Heyden et al. introduced an iterative factorization method for projective reconstruction from image sequences. In their formulation, the projective structure and motion are computed by using an iterative factorization based on 4D subspace. In this paper, the problem is reformulated based on fact that the x, y, and z coordinates of each feature in projective space are known from their projection. The projective reconstruction, i.e., the relative depths w and the 3D motion, is obtained by a simple iterative factorization based on 1D subspace. This allows the use of very fast algorithms even when using a large number of features and large number of frames. The experiments with both simulate and real data show that the method presented in the paper is efficient and has good convergency.
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  • School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049 China
Bibliografia
  • [1] M. Tomaszewski and W. Skarbek: On projection matrix identification for camera calibration. Proc. 2nd Int. Conf. on Computer Vision Theory and Applications, Barcelona, 92-100, 2007.
  • [2] W. Skarbek and M. Tomaszewski: Epipolar angular factorisation of essential matrix for camera pose calibration. MIRAGE09, Lect. Notes Comput. Sc. 5496, 401-412, 2009.
  • [3] Y. Peng, S. Liu, and F. Liu: Projective reconstruction with occlusions. Opto-Electron. Rev. 18, 150-154, 2010.
  • [4] A. Makadia, C. Geyer, and K. Daniilidis: Correspondenceless structure from motion. Int. J. Comput. Vision 75, 311-332, 2007.
  • [5] R. Vidal and R. Hartley: Three-view multibody structure from motion. IEEE T. Pattern Anal. 30, 214-227, 2008.
  • [6] W. Tang and Y. Hung: A subspace method for projective reconstruction from multiple images with missing data. Image Vision Comput. 24, 515-524, 2006.
  • [7] C. Tomasi and T. Kanade: Shape and motion from image streams under orthography: A factorization method. Int. J. Comput. Vision 9, 137-154, 1992.
  • [8] P. Sturm and B. Triggs: A factorization based algorithm for multi-image projective structure and motion. ECCV'96, Lect. Notes Comput. Sc. 1065, 709-720, 1996.
  • [9] A. Heyden, R. Berthilsson, and G. Sparr: An iterative factorization method for projective structure and motion from image sequences. Image Vision Comput. 17, 981-991, 1999.
  • [10] S. Mahamud and M. Hebert: Iterative projective reconstruction from multiple views. Proc. CVPR IEEE 2, 430-437, 2000.
  • [11] H. Ackermann and K. Kanatani: Iterative low complexity factorization for projective reconstruction. Proc. 2nd Workshop on Robot Vision, Auckland, 153-164, 2008.
  • [12] P. Aguiar and J. Moura: Factorization as a Rank 1 Problem. Proc. CVPR IEEE 1, 178-184, 1999.
  • [13] S. Liu, C. Wu, L. Tang, and J. Jia: An iterative factorization method based on Rank 1 for projective structure and motion. IEICE T. Inf. Syst. 9, 2183-2188, 2005.
  • [14] W. Skarbek: Singular and principal subspace of signal information system by BROM algorithm. RSKT'07, Lect. Notes Artif. Int. 4481, 157-165, 2007.
  • [15] H. Ackermann and K. Kanatani: Fast projective reconstruction: Toward ultimate efficiency. IPSJ T. Comput. Vision Image Media 49, 68-78, 2008.
  • [16] H. Ackermann and K. Kanatani: Robust and efficient 3D reconstruction by self-calibration. Proc. IAPR Conf. on Machine Vision Applications, Tokyo, 178-181, 2007.
  • [17] K. Zhang, L. Zhang, H. Song, and W. Zhou: Active contours with selective local or global segmentation: a new formulation and level set method. Image Vision Comput. 28, 668-676, 2010.
  • [18] K. Zhang, H. Song, and L. Zhang: Active contours driven by local image fitting energy. Pattern Recogn. 43, 1199-1206, 2010.
  • [19] J. Ning, L. Zhang, D. Zhang, and C. Wu: Interactive image segmentation by maximal similarity based region merging. Pattern Recogn. 43, 445-456, 2010.
  • [20] K. Zhang, L. Zhang, and S. Zhang: A variational multiphase level set approach to simultaneous segmentation and bias correction. The Int. Conf. on Image Processing 1, 1-4, 2010.
  • [21] J. Ning, L. Zhang, D. Zhang, and C. Wu: Robust object tracking using joint colour-texture histogram. Int. J. Pattern Recogn. 23, 1245-1263, 2009.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWAD-0020-0015
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