Abstract
Correlation-based stereo matching is very important to the generation of 3D terrain model. One of the difficulties in this stereo matching is the selection of the window size, since there are two competing factors that must be balanced in any stereo reconstruction process – perspective distortion and stereo matching error. This paper presents how the correlation window size affects the accuracy of stereo matching and suggests a tool to tune the window size in a given image domain. To facilitate the analysis proposed in this paper, we use photo-realistic simulation methodology to generate a pair of photo-realistic synthetic images of the terrain from a pre-acquired DEM(Digital Elevation Map) and ortho-image, which can be served as the pseudo ground truth. We performed 3D reconstruction on synthetic images of a natural terrain with Terrest system and carried out the evaluation of the correlation window on DEM accuracy. Experimental results are consistent with our strong expectation about two competing factors and show that our approach can be a useful tool to tune the window size.
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References
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)
Ayache, N., Faverjon, B.: Efficient Registration of Stereo Images by Matching Graph Description of Edge Segments. Int’l. J. Computer Vision, 107–131 (1987)
Agouris, P., Schenk, T.: Automates Aerotriangulation Using Multiple Image Multipoint Matching. Photogrammetric Engineering and Remote Sensing LXII, 703–710 (1996)
Fua, P., Leclerc, Y.G.: Taking Advantage of Image Based and Geometry Based Constraints to Recover 3D Surfaces. Computer Vision and Image Understanding 64, 111–127 (1996)
Hannah, M.: A System for Digital Stereo Image Matching. Photogrammetric Engineering and Remote Sensing 55, 1765–1770 (1989)
Panton, D.J.: A Flexible Approach to Digital Stereo Mapping. Photogrammetric Engineering and Remote Sensing 44, 1499–1512 (1978)
Cochran, S.D., Medioni, G.: 3-D Surface Description from Binocular Stereo. IEEE Trans. Pattern Analysis and Machine Intelligence 14, 981–994 (1992)
Mori, K., Kidode, K., Asada, H.: An Interative Prediction and Correction Method for Automatic Stereo Comparison. Computer Graphics and Image Processing 2, 393–401 (1973)
Mostafavi, H.: Image Correlation with Geometric Distortion Part II: Effects on Local Accuracy. IEEE Trans. Aerospace and Electronic 14, 494–500 (1978)
Schultz, H., Woo, D., Riseman, E., Stolle, F.: Error Detection and DEM Fusion Using Self-consistency. In: IEEE Int. Conf. on Computer Vision, vol. 2, pp. 1174–1181 (1999)
Scharstein, D., Szeliski, R.: A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms. International Journal of Computer Vision 47, 7–42 (2002)
Schultz, H.: Terrain Reconstruction from Widely Separated Images. In: Proceeding of SPIE, vol. 2486, pp. 113–122 (1995)
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© 2004 Springer-Verlag Berlin Heidelberg
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Woo, DM., Schultz, H., Riseman, E., Hanson, A. (2004). Performance of Correlation-Based Stereo Algorithm with Respect to the Change of the Window Size. In: Aizawa, K., Nakamura, Y., Satoh, S. (eds) Advances in Multimedia Information Processing - PCM 2004. PCM 2004. Lecture Notes in Computer Science, vol 3332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30542-2_96
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DOI: https://doi.org/10.1007/978-3-540-30542-2_96
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23977-2
Online ISBN: 978-3-540-30542-2
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