Abstract
In this paper, we propose a shadow-free TILT method to rectify facade images corrupted by shadows. The proposed method is deduced from the original TILT, and improve it by introducing a multiplicative shadow factor. That is, in our method, the constraint is represented that the rectified image equals to the low-rank image multiplied by the shadow image, yet with the additive noise corruption. Moreover, the objective function is improved by incorporating the smooth shadow model. Experimental results on both synthetic and real images demonstrate that our method provides more accurate and stable rectification results as compared with the original TILT, especially when shadows are strong in the input images.
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
Dick, A.R., Torr, P.H.S., Cipolla, R.: Modelling and interpretation of architecture from several images. Inter. J. of Computer Vision 60, 111–134 (2004)
Xiao, J., Fang, T., Tan, P., Zhao, P., Ofek, E., Quan, L.: Image-based facade modeling. ACM Transaction on Graphics 27, 161:1–161:10 (2008)
Xiao, J., Fang, T., Zhao, P., Lhuillier, M., Quan, L.: Image-based street-side city modeling. ACM Transaction on Graphics 28, 114:1–114:12 (2009)
Hong, W.: On symmetry and multiple-view geometry: Structure, pose, and calibration from a single image. Inter. J. of Computer Vision 60 (2004)
Müller, P., Wonka, P., Haegler, S., Ulmer, A., Van Gool, L.: Procedural modeling of buildings. ACM Transaction on Graphics 25, 614–623 (2006)
Zhao, P., Quan, L.: Translation symmetry detection in a fronto-parallel view. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1009–1016 (2011)
Teboul, O., Simon, L., Koutsourakis, P., Paragios, N.: Segmentation of building facades using procedural shape priors. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3105–3112 (2010)
Wu, C., Frahm, J.-M., Pollefeys, M.: Detecting Large Repetitive Structures with Salient Boundaries. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part II. LNCS, vol. 6312, pp. 142–155. Springer, Heidelberg (2010)
Micusk, B., Wildenauer, H., Kosecka, J.: Detection and matching of rectilinear structures. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–7 (2008)
Tuytelaars, T., Proesmans, M., Gool, L.J.V.: The cascaded hough transform as support for grouping and finding vanishing points and lines. In: Proceedings of the International Workshop on Algebraic Frames for the Perception-Action Cycle, pp. 278–289 (1997)
Tuytelaars, T., Gool, L.V., Proesmans, M., Moons, T., Mi, E.: The cascaded hough transform as an aid in aerial image interpretation. In: International Conference on Computer Vision, pp. 67–72 (1998)
Peng, Y., Ganesh, A., Wright, J., Xu, W., Ma, Y.: Rasl: Robust alignment by sparse and low-rank decomposition for linearly correlated images. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 763–770 (2010)
Wagner, A., Wright, J., Ganesh, A., Zhou, Z., Mobahi, H., Ma, Y.: Towards a practical face recognition system: Robust alignment and illumination via sparse representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 34, 372–386 (2012)
Candès, E.J., Li, X., Ma, Y., Wright, J.: Robust principal component analysis? Clinical Orthopaedics and Related Research abs/0912.3599, 1–39 (2009)
Zhang, Z., Liang, X., Ganesh, A., Ma, Y.: TILT: Transform Invariant Low-Rank Textures. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) ACCV 2010, Part III. LNCS, vol. 6494, pp. 314–328. Springer, Heidelberg (2011)
Mobahi, H., Zhou, Z., Yang, A.Y., Ma, Y.: Holistic 3d reconstruction of urban structures from low-rank textures. In: International Conference on Computer Vision Workshops, pp. 593–600 (2011)
Lin, Z., Ganesh, A., Wright, J., Wu, L., Chen, M., Ma, Y.: Fast convex optimization algorithms for exact recovery of a corrupted low-rank matrix. In: Intl. Workshop on Comp. Adv. in Multi-Sensor Adapt. Processing, Aruba, Dutch Antilles, pp. 213–216 (2009)
Lin, Z., Chen, M., Wu, L.: The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices. Analysis math.OC, 2209–2215 (2010)
Cai, J.F., Candès, E.J., Shen, Z.: A singular value thresholding algorithm for matrix completion. SIAM J. on Optimization 20, 1956–1982 (2010)
Hale, E.T., Yin, W., Zhang, Y.: Fixed-point continuation for 1-minimization: Methodology and convergence. SIAM J. on Optimization 19, 1107–1130 (2008)
He, K., Sun, J., Tang, X.: Guided Image Filtering. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part I. LNCS, vol. 6311, pp. 1–14. Springer, Heidelberg (2010)
Shao, H., Svoboda, T., Gool, L.V.: ZuBuD — Zürich buildings database for image based recognition. Technical Report 260, Computer Vision Laboratory, Swiss Federal Institute of Technology (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, L., Yan, H., Wang, L., Pan, C. (2013). Shadow-Free TILT for Facade Rectification. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds) Computer Vision – ACCV 2012. ACCV 2012. Lecture Notes in Computer Science, vol 7727. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37447-0_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-37447-0_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37446-3
Online ISBN: 978-3-642-37447-0
eBook Packages: Computer ScienceComputer Science (R0)