Abstract
This paper presents an approach to derive the equations of planar patches given a stereo pair of wide baseline or sparse view images. The algorithm starts by detecting junctions in both images using the so-called JUDOCA operator. A transformation matrix can be estimated using the junction attributes. In addition, a rough estimate for the fundamental matrix can be obtained to guide a matching process between the two views. Triangulation is used to reconstruct the locations of 2-edge junctions in space as well as to obtain the equations of 3D lines forming the junctions. This is done by obtaining four planes going through the projections of the junction edges and the optical centers. The equations of the 3D lines are used to get the equation of the plane of the junction.
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References
Kanazawa, Y., Uemura, K.: Wide Baseline Matching using Triplet Vector Descriptor. In: Proc. BMVC, Edinburgh, UK, vol. I, pp. 267–276 (2006)
Bay, H., Ferrari, V., Gool, L.V.: Wide-Baseline Stereo Matching with Line Segments. In: Proc. CVPR, San Diego, CA, USA, vol. 1, pp. 329–336 (2005)
Lowe, D.: Object recognition from local scale invariant features. In: Proc. ICCV, Kerkyra, Greece, vol. 2, pp. 1150–1157 (1999)
Andreasson, H., Treptow, A., Duckett, T.: Localization for mobile robots using panoramic vision, local features and particle filters. In: Proc. ICRA, Barcelona, Spain, pp. 3348–3353 (2005)
Tuytelaars, T., Gool, L.V.: Matching Widely Separated Views based on Affine Invariant Regions. IJCV 59, 61–85 (2004)
Elias, R.: Wide baseline matching through homographic transformation. In: Proc. ICPR, Washington, DC, USA, vol. 4, pp. 130–133. IEEE Computer Society Press, Los Alamitos (2004)
Laganière, R., Elias, R.: The Detection of Junction Features in Images. In: Proc. ICASSP, Montréal, Québec, Canada, vol. III, pp. 573–576. IEEE, Los Alamitos (2004)
Elias, R.: Modeling of Enivornments: From Sparse Views to Obstacle Reconstruction. LAP Lambert Academic Publishing, Germany (2009) ISBN: 3838322207
Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2004) ISBN: 0521540518
Elias, R.: Geometric modeling in computer vision: An introduction to projective geometry. In: Wah, B. (ed.) Wiley Encyclopedia of Computer Science and Engineering, vol. 3, pp. 1400–1416. John Wiley & Sons, Inc., Chichester (2008)
Laganière, R., Labonté, F.: Stereokineopsis: A survey. Technical Report CRPR-RT-9603, École Polytechnique de Montréal, Groupe de Recherche en Perception et Robotique (1996)
Beardsley, P., Zisserman, A., Murray, D.: Sequential update of projective and affine structure from motion. IJCV 23, 235–259 (1997)
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Elias, R. (2010). Inferring Planar Patch Equations from Sparse View Stereo Images. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6454. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17274-8_16
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DOI: https://doi.org/10.1007/978-3-642-17274-8_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17273-1
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