Application of Computer Vision Methods and Algorithms in Documentation of Cultural Heritage


  • David Káňa Geodis Brno, ltd, Lazaretní 11a, Brno, Czech Republic
  • Vlastimil Hanzl Brno University of Technology, Faculty of Civil Engineering, Veveří 331/98, Brno, Czech Re



computer vision, interest operator, matching


The main task of this paper is to describe methods and algorithms used in computer vision for fully automatic reconstruction of exterior orientation in ordered and unordered sets of images captured by digital calibrated cameras without prior informations about camera positions or scene structure. Attention will be paid to the SIFT interest operator for finding key points clearly describing the image areas with respect to scale and rotation, so that these areas could be compared to the regions in other images. There will also be discussed methods of matching key points, calculation of the relative orientation and strategy of linking sub-models to estimate the parameters entering complex bundle adjustment. The paper also compares the results achieved with above system with the results obtained by standard photogrammetric methods in processing of project documentation for reconstruction of the Žinkovy castle.


Lowe, D.: Sift demo implementation.

Lowe, D.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60, 2 (2004), p. 91-110.

Harris, C. G.; Stephens, M. J.: A combined corner and edge detector. Proceeding Fourth

Alvey Vision Conference, 1988, p. 147 - 151.

Changchang Wu; SIFT on GPU. University of North Carolina at Chapel Hill,

Hartley, R.I.; Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, June 2000.

Hartley, R.I.: An investigation of the Essential Matrix. 1993. http://users.rsise.anu.

Manolis I. A. Lourakis; Antonis A. Argyros, SBA: A software package for generic sparse bundle adjustment, ACM Transactions on Mathematical Software (TOMS), v.36 n.1, March 2009, pp.1-30,

Brown, M.; Szeliski, R.; Winder, S.: Multi-image Matching Using Multi-scale Oriented Patches. Proc. Int. Conf. on Computer Vision and Pattern Recognition, San Diego, 2005, pp.510-517.

B. Triggs, P. McLauchlan, R. Hartley, and A. Fitzgibbon. Bundle adjustment -a modern synthesis. Vision Algorithms: Theory and Practice, pages 298–372, 1999.

Manolis I. A. Lourakis: A brief description of the Levenberg-Marquardt algorithm by levmar,, July 2004

Hartley R.I.: In defence of the 8-point algorithm, ICCV, pp.1064, Fifth International Conference on Computer Vision (ICCV'95), 1995