Abstract
We present a new hybrid stereo matching technique in terms of the co-operation of area-based stereo and feature-based stereo to build 3D site model from urban images. The core of our technique is that feature matching is carried out by the reference of the disparity evaluated by area-based stereo. Since the reference of the disparity can significantly reduce the number of feature matching combinations, feature matching error can be drastically minimized. One requirement of the disparity to be referenced is that it should be reliable to be used in feature matching. To measure the reliability of the disparity, in this paper, we employ the self-consistency of the disparity. Our suggested technique is applied to the detection of 3D line segments by 2D line matching using our hybrid stereo matching, which can be efficiently utilized in the generation of the rooftop model from urban images. Since occlusions are occurred around the outlines of buildings, we use multi-image stereo scheme by fusing 3D line segments extracted from several pairs of stereo images. The suggested method is evaluated on Avenches data set of Ascona aerial images. Experimental results indicate that the extracted 3D line segments have an average error of 0.5m and can be efficiently used to the construction of 3D site models using a simple 3D line grouping.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Panton, D.J.: A Flexible Approach to Digital Stereo Mapping. Photogrammetric Engineering and Remote Sensing 44, 1499–1512 (1978)
Mostafavi, H.: Image Correlation with Geometric Distortion Part II: Effects on Local Accuracy. IEEE Trans. Aerospace and Electronic 14, 494–500 (1978)
Grimson, W.: Computational Experiments with Feature Based Stereo Algorithm. IEEE Trans. Pattern Analysis and Machine Intelligence 7, 17–23 (1985)
Marr, D., Poggio, T.: A Computational Theory of Human Stereo Vision. Proc. Royal Society of London 204 of B, 301–328 (1979)
Kanade, T., Okutomi, M.: A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment. IEEE Trans. Pattern Analysis and Machine Intelligence 16, 920–932 (1994)
Han, K., Bae, T., Ha, Y.: Hybrid Stereo Matching with a New Relaxation Scheme of Preserving Disparity Discontinuity. Pattern Recognition 33, 767–785 (2000)
Leclerc, Y., Luong, Q., Fua, P.: Self-consistency: A Novel Approach to Characterizing the Accuracy and Reliability of Point Correspondence Algorithms. In: DARPA Image Understanding Workshop (1998)
Schultz, H., Hanson, A., Riseman, E., Stolle, F., Zhu, Z., Woo, D.: A Self-consistency Technique for Fusing 3D Information. In: Proc. Information Fusion, pp. 1106–1112 (2002)
Boldt, M., Weiss, R., Riseman, E.: Token-based Extraction of Straight Lines. IEEE Trans. Systems Man Cybernetics 19, 1581–1594 (1989)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Woo, DM., Schultz, H., Jung, YK., Lee, KW. (2004). Generation of 3D Urban Model Using Cooperative Hybrid Stereo Matching. In: Aizawa, K., Nakamura, Y., Satoh, S. (eds) Advances in Multimedia Information Processing - PCM 2004. PCM 2004. Lecture Notes in Computer Science, vol 3331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30541-5_28
Download citation
DOI: https://doi.org/10.1007/978-3-540-30541-5_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23974-1
Online ISBN: 978-3-540-30541-5
eBook Packages: Computer ScienceComputer Science (R0)