Abstract
Several image mosaicing algorithms claiming to advance the state of the art have been proposed so far. Though sometimes improvements can be recognised without quantitative evidences, the importance of a principled methodology to compare different algorithms is essential as this discipline evolves. Which is the best? What means the best? How to ascertain the supremacy? To answer such questions, in this paper we propose an evaluation methodology including standard data sets, ground-truth information and performance metrics. We also compare three variants of a well-known mosaicing algorithm according to the proposed methodology.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Sawhney, H., Hsu, S., Kumar, R.: Robust video mosaicing through topology inference and local to global alignment. In: Burkhardt, H., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1407. Springer, Heidelberg (1998)
Shum, H.-Y., Szeliski, R.: Systems and experiment paper: Construction of panoramic image mosaics with global and local alignment. Int. J. of Computer Vision 36(2), 101–130 (2000)
Brown, M., Lowe, D.G.: Automatic panoramic image stitching using invariant features. Int. J. Computer Vision 74(1), 59–73 (2007)
Bevilacqua, A., Azzari, P.: High-quality real time motion detection using ptz cameras. In: Proc. Intl. Conf. on AVSS, p. 23 (2006)
Irani, M., Anandan, P., Bergen, J.R., Kumar, R., Hsu, S.: Efficient representations of video sequences and their applications. SP: Image Communication 8(4), 327–351 (1996)
Kelly, A.: Mobile robot localization from large-scale appearance mosaics. Int. J. Robotic Res. 19(11), 1104–1125 (2000)
Capel, D., Zisserman, A.: Computer vision applied to super resolution. IEEE Signal Processing Magazine 20(3), 75–86 (2003)
Azzari, P., Di Stefano, L., Tombari, F., Mattoccia, S.: Markerless augmented reality using image mosaics. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D. (eds.) ICISP 2008. LNCS, vol. 5099. Springer, Heidelberg (2008)
Scharstein, D., Szeliski, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. Int. J. Computer Vision 47(1-3), 7–42 (2002)
Baker, S., Scharstein, D., Lewis, J.P., Roth, S., Black, M., Szeliski, R.: A database and evaluation methodology for optical flow. In: Proc. IEEE ICCV (October 2007)
Brown, L.G.: A survey of image registration techniques. ACM Computing Surveys 24(4), 325–376 (1992)
Zitova, B., Flusser, J.: Image registration methods: a survey. Image and Vision Computing 21(11), 977–1000 (2003)
PoV-Ray. Persistence of vision raytracer
Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. on PAMI 22(11), 1330–1334 (2000)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2003)
Hess, R., Fern, A.: Improved video registration using non-distinctive local image features. In: Proc. IEEE Conf. on CVPR (2007)
Nasa© Earth Observatory. Picture of the day gallery
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Azzari, P., Di Stefano, L., Mattoccia, S. (2008). An Evaluation Methodology for Image Mosaicing Algorithms. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2008. Lecture Notes in Computer Science, vol 5259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88458-3_9
Download citation
DOI: https://doi.org/10.1007/978-3-540-88458-3_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88457-6
Online ISBN: 978-3-540-88458-3
eBook Packages: Computer ScienceComputer Science (R0)