Abstract
In this paper, we introduce a simple but efficient cue for the extraction of shadows from a single color image, the bright channel cue. We discuss its limitations and offer two methods to refine the bright channel: by computing confidence values for the cast shadows, based on a shadow-dependent feature, such as hue; and by combining the bright channel with illumination invariant representations of the original image in a flexible way using an MRF model. We present qualitative and quantitative results for shadow detection, as well as results in illumination estimation from shadows. Our results show that our method achieves satisfying results despite the simplicity of the approach.
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Salvador, E., Cavallaro, A., Ebrahimi, T.: Cast shadow segmentation using invariant color features. Computer Vision and Image Understanding 95, 238–259 (2004)
Levin, A., Lischinski, D., Weiss, Y.: A closed-form solution to natural image matting. IEEE Transactions on Pattern Analysis and Machine Intelligence 30, 228–242 (2008)
Finlayson, G., Drew, M., Lu, C.: Intrinsic Images by Entropy Minimization. In: Pajdla, T., Matas, J. (eds.) ECCV 2004. LNCS, vol. 3023, pp. 582–595. Springer, Heidelberg (2004)
Finlayson, G., Hordley, S., Lu, C., Drew, M.: On the removal of shadows from images. IEEE Transactions on Pattern Analysis and Machine Intelligence 28, 59–68 (2006)
Shor, Y., Lischinski, D.: The shadow meets the mask: Pyramid-based shadow removal. Computer Graphics Forum 27, 577–586 (2008)
Zhu, J., Samuel, K.G.G., Masood, S., Tappen, M.F.: Learning to recognize shadows in monochromatic natural images. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 (2010)
He, K., Sun, J., Tang, X.: Single image haze removal using dark channel prior. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR (2009)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 3rd edn. Prentice-Hall, Inc. (2006)
Gevers, T., Smeulders, A.W.M.: Color based object recognition. Pattern Recognition 32, 453–464 (1997)
Geusebroek, J.M., van den Boomgaard, R., Smeulders, A.W.M., Geerts, H.: Color invariance. IEEE Transactions on Pattern Analysis and Machine Intelligence 23, 1338–1350 (2001)
van de Weijer, J., Gevers, T., Geusebroek, J.M.: Edge and corner detection by photometric quasi-invariants. IEEE Transactions on Pattern Analysis and Machine Intelligence 27 (2005)
Diplaros, A., Gevers, T., Patras, I.: Combining color and shape information for illumination-viewpoint invariant object recognition. IEEE Trans. on Image Processing 15, 1–11 (2006)
Boykov, Y., Funka-lea, G.: Graph cuts and efficient n-d image segmentation. International Journal of Computer Vision 70, 109–131 (2006)
Kolmogorov, V.: Convergent tree-reweighted message passing for energy minimization. IEEE Transactions on Pattern Analysis and Machine Intelligence 28, 1568–1583 (2006)
Hammer, P.L., Hansen, P., Simeone, B.: Roof duality, complementation and persistency in quadratic 0-1 optimization. Mathematical Programming 28, 121–155 (1984)
Kolmogorov, V., Rother, C.: Minimizing nonsubmodular functions with graph cuts-a review. IEEE Transactions on Pattern Analysis and Machine Intelligence 29, 1274–1279 (2007)
Lempitsky, V., Rother, C., Roth, S., Blake, A.: Fusion moves for markov random field optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence 32, 1392–1405 (2010)
Sato, I., Sato, Y., Ikeuchi, K.: Illumination from shadows. IEEE Transactions on Pattern Analysis and Machine Intelligence 25, 290–300 (2003)
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Panagopoulos, A., Wang, C., Samaras, D., Paragios, N. (2012). Estimating Shadows with the Bright Channel Cue. In: Kutulakos, K.N. (eds) Trends and Topics in Computer Vision. ECCV 2010. Lecture Notes in Computer Science, vol 6554. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35740-4_1
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DOI: https://doi.org/10.1007/978-3-642-35740-4_1
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