On Line-based Homographies in Urban Environments
Nils Hering, Lutz Priese, Frank Schmitt
2013
Abstract
This paper contributes to matching and registration in urban environments. We develop a new method to extract only those line segments that belong to contours of buildings. This method includes vanishing point detection, removal of wild structures, sky and roof detection. A registration of two building facades is achieved by computing a line-based homography between both. The known crucial instability of line homography is overcome with a line-panning and iteration technique. This homography approach is also able to separate single facades in a building.
References
- Baltsavias, E. P. (2004). Object extraction and revision by image analysis using existing geodata and knowledge: current status and steps towards operational systems. ISPRS Journal of Photogrammetry and Remote Sensing, 58(3-4):129 - 151. Integration of Geodata and Imagery for Automated Refinement and Update of Spatial Databases.
- Bay, H., Ferrari, V., and Van Gool, L. (2005). Wide-baseline stereo matching with line segments. In Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01, CVPR 7805, pages 329-336, Washington, DC, USA. IEEE Computer Society.
- Canny, J. (1986). A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell., 8(6):679-698.
- David, P. (2008). Detection of building facades in urban environments. In Rahman, Z.-u., Reichenbach, S. E., and Neifeld, M. A., editors, Visual Information Processing XVII, volume 6978 of Proceedings of the SPIE, pages 69780P-69780P-11.
- Dubrofsky, E. and Woodham, R. J. (2008). Combining line and point correspondences for homography estimation. In Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II, ISVC 7808, pages 202-213, Berlin, Heidelberg. SpringerVerlag.
- Fischler, M. A. and Bolles, R. C. (1981). Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM, 24(6):381-395.
- Guerrero, J. and Sags, C. (2003). Robust line matching and estimate of homographies simultaneously. In Perales, F., Campilho, A., Blanca, N., and Sanfeliu, A., editors, Pattern Recognition and Image Analysis, volume 2652 of Lecture Notes in Computer Science, pages 297-307. Springer Berlin Heidelberg.
- Hartley, R. I. and Zisserman, A. (2004). Multiple View Geometry in Computer Vision. Cambridge University Press, ISBN: 0521540518, second edition.
- Horowitz, S. L. and Pavlidis, T. (1976). Picture segmentation by a tree traversal algorithm. J. ACM, 23(2):368- 388.
- Iqbal, Q. and Aggarwall, J. K. (1999). Applying perceptual grouping to content-based image retrieval:building images. In Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on., volume 1, Fort Collins, CO, USA.
- Kumar, S. and Hebert, M. (2003). Man-made structure detection in natural images using a causal multiscale random field. In Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on, volume 1, pages 119-126.
- Leavers, V. F. and Boyce, J. F. (1987). The radon transform and its application to shape parametrization in machine vision. Image Vision Comput., 5(2):161-166.
- Lowe, D. (2003). Distinctive image features from scaleinvariant keypoints. In International Journal of Computer Vision, volume 20, pages 91-110.
- M. Kuwahara, K. Hachimura, S. Eiho, and M. Kinoshita (1976). Processing of ri-angiocardiographic images. In Preston, K. and Onoe, M., editors, Digital Processing of Biomedical Images, pages 187-202.
- Mayer, H. (1999). Automatic object extraction from aerial imagery-a survey focusing on buildings. Computer Vision and Image Understanding, 74(2):138 - 149.
- Priese, L. and Rehrmann, V. (1993). A fast hybrid color segmentation method. In S.J. Pppl, H. Handels, editor, Proc. DAGM Symposium Mustererkennung, Informatik Fachberichte, Springer Verlag, pages 297-304.
- Priese, L., Schmitt, F., and Hering, N. (2009). Grouping of semantically similar image positions. In Salberg, A.-B., Hardeberg, J. Y., and Jenssen, R., editors, 16th Scandinavian Conference, SCIA 2009, Oslo, Norway, June 15-18, Proceedings, volume 5575, pages 726- 734.
- Schmid, C. and Zisserman, A. (1997). Automatic line matching across views. In Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on, pages 666 -671.
- Schmitt, F. and Priese, L. (2009a). Intersection point topology for vanishing point detection. In Accepted for publication in: Discrete Geometry for Computer Imagery 2009, Montreal, Canada.
- Schmitt, F. and Priese, L. (2009b). Sky detection in cscsegmented color images. In Fourth International Conference on Computer Vision Theory and Applications (VISAPP) 2009, Lisboa, Portugal, volume 2, pages 101-106.
- Zhang, W. and Kos?ecká, J. (2007). Hierarchical building recognition. Image Vision Comput., 25(5):704-716.
Paper Citation
in Harvard Style
Hering N., Priese L. and Schmitt F. (2013). On Line-based Homographies in Urban Environments . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, pages 358-369. DOI: 10.5220/0004293603580369
in Bibtex Style
@conference{visapp13,
author={Nils Hering and Lutz Priese and Frank Schmitt},
title={On Line-based Homographies in Urban Environments},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={358-369},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004293603580369},
isbn={978-989-8565-47-1},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - On Line-based Homographies in Urban Environments
SN - 978-989-8565-47-1
AU - Hering N.
AU - Priese L.
AU - Schmitt F.
PY - 2013
SP - 358
EP - 369
DO - 10.5220/0004293603580369