Browse > Article
http://dx.doi.org/10.6109/jkiice.2016.20.3.527

Uncertainty Analysis of Observation Matrix for 3D Reconstruction  

Koh, Sung-shik (Mobile Comm., Samsung Electronics Co., Ltd.)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.20, no.3, 2016 , pp. 527-535 More about this Journal
Abstract
Statistical optimization algorithms have been variously developed to estimate the 3D shape and motion. However, statistical approaches are limited to analyze the sensitive effects of SfM(Shape from Motion) according to the camera's geometrical position or viewing angles and so on. This paper propose the quantitative estimation method about the uncertainties of an observation matrix by using camera imaging configuration factors predict the reconstruction ambiguities in SfM. This is a very efficient method to predict the final reconstruction performance of SfM algorithm. Moreover, the important point is that our method show how to derive the active guidelines in order to set the camera imaging configurations which can be expected to lead the reasonable reconstruction results. The experimental results verify the quantitative estimates of an observation matrix by using camera imaging configurations and confirm the effectiveness of our algorithm.
Keywords
3D Reconstruction; Observation Matrix; Uncertainty Analysis; Noise Estimation; Camera Configuration;
Citations & Related Records
연도 인용수 순위
  • Reference
1 C. Wu. "Towards linear-time incremental structure from motion," In Proceeding of 2013 International Conference on 3D Vision, pp.127-134, Seattle, USA, Jun. 2013.
2 P. A. Beardsley, A. Zisserman, and D. W. Murray, "Sequential updating of projective and affine structure from motion," International Journal of Computer Vision, vol.23, no.3, pp.235-259, Jun.-Jul. 1997.   DOI
3 J. Heller, M. Havlena, M. Jancosek, A. Torii, and T. Pajdla, "3D Reconstruction from Photographs by CMP SfM Web Service," In Proceeding of 14th IAPR International Conference on Machine Vision Applications, Tokyo, Japan, pp. 30-34, May, 2015.
4 M. Jancosek and T. Pajdla. "Multi-view reconstruction preserving weakly-supported surfaces," In Proceeding of 2011 IEEE Conference on CVPR, pp. 3121-3128, New York, USA, Jun. 2011.
5 B. Triggs, P. McLauchlan, R. Hartley, and A. Fitzgibbon: "Bundle adjustment-A modern synthesis, in Vision Algorithms: Theory and Practice," Lecture Notes in Computer Science, Springer-Verlag, vol.1883, pp.298-372, Jan. 2000.
6 J. Oliensis. "The least-squares error for structure from infinitesimal motion," International Journal of Computer Vision, vol.61, no.3, pp.259-299, Feb. 2005.   DOI
7 Zhaohui Sun, Visvanathan Ramesh, A. Murat Tekalp, "Error Characterization of the Factor-ization method," Computer Vision and Image Understanding. vol.82, no2, pp.110-137, Nov. 2001.   DOI
8 M. Spetsakis, "Models of statistical visual motion estimation," Computer Vision, Graphics, and Image Processing, vol.60, no.3, pp.300-312, Nov. 1994.   DOI
9 K. Daniilidis and H.-H. Nagel, "Analytical results on error sensitivity of motion estimation from two views," Image and Vision Computing, vol.8, no.4, pp.297-303, Nov. 1990.   DOI
10 A. Chiuso, R. Brockett, and S. Soatto. "Optimal structure from motion:Local ambiguities and global estimates," International Journal of Computer Vision, vol.39, no.3, pp.195-228, Sep. 2000.   DOI
11 G.-S.J. Young and R.: Chellappa, "Statistical analysis of inherent ambiguities in recovering 3-d motion from a noisy flow field," IEEE Transactions on PAMI, vol.14, no.10, pp.995- 1013, Oct. 1992.   DOI
12 K. Kanatani, "Unbiased estimation and statistical analysis of 3-d rigid motion from two views," IEEE Transactions on PAMI, vol.15, no.1, pp.37-50, Jan. 1993.   DOI
13 R. Szeliski and S. B. Kang, "Shape ambiguities in structure-from-motion," IEEE Transactions on PAMI, vol.19, no.1, pp.506-512, May 1997.   DOI
14 J. Oliensis, "A New Structure-from-Motion Ambiguity," IEEE Transactions on PAMI, vol.22, no.7, pp.685-700, Jul. 2000.   DOI
15 J. Weng, N. Ahuja, and T.S. Huang, "Optimal motion and structure estimation," IEEE Transactions on PAMI, vol.15, no.9, pp.864-884, Sep. 1993.   DOI
16 C. Tomasi and T. Kanade, "Shape and motion from image streams under orthography: A factorization method," International Journal of Computer Vision, vol.9, no.9, pp.137-154, Nov. 1992.   DOI
17 R. Szeliski and S. B. Kang, "Recovering 3D shape and motion from image streams using nonlinear least squares," Journal of Visual Communication and Image Representation, 5, no.1, pp10-28, Mar. 1994.   DOI