Abstract
Although shape from shading (SfS) has been studied for almost four decades, the performance of most methods applied to real-world images is still unsatisfactory: This is often caused by oversimplified reflectance and projection models as well as by ignoring light attenuation and nonconstant albedo behavior. We address this problem by proposing a novel approach that combines three powerful concepts: (i) By means of a Chan-Vese segmentation step, we partition the image into regions with homogeneous reflectance properties. (ii) This homogeneity is further improved by an adaptive thresholding that singles out unreliable details which cause fluctuating albedos. Using an inpainting method based on edge-enhancing anisotropic diffusion, structures are filled in such that the albedo does no longer suffer from fluctuations. (iii) Finally a sophisticated SfS method is used that features a perspective projection model, considers physical light attenuation and models specular highlights. In our experiments we demonstrate that each of these ingredients improves the reconstruction quality significantly. Their combination within a single method gives favorable perfomance also for images that are taken under real-world conditions where simpler approaches fail.
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References
Seitz, S.M., Curless, B., Diebel, J., Scharstein, D., Szeliski, R.: A comparison and evaluation of multi-view stereo reconstruction algorithms. In: Proc. 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 519–528. IEEE Computer Society Press, New York (2006)
Horn, B.K.P.: Obtaining shape from shading information. In: Winston, P.H. (ed.) The Psychology of Computer Vision, pp. 115–155. McGraw-Hill, New York (1975)
Zhang, R., Tsai, P.S., Cryer, J.E., Shah, M.: Shape from shading: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(8), 690–706 (1999)
Prados, E., Faugeras, O.: Shape from shading: A well-posed problem? In: Proc. 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 870–877. IEEE Computer Society Press, San Diego (2005)
Tankus, A., Sochen, N., Yeshurun, Y.: Shape-from-shading under perspective projection. International Journal of Computer Vision 63(1), 21–43 (2005)
Cristiani, E., Falcone, M., Seghini, A.: Some remarks on perspective shape-from-shading models. In: Sgallari, F., Murli, A., Paragios, N. (eds.) SSVM 2007. LNCS, vol. 4485, pp. 276–287. Springer, Heidelberg (2007)
Ahmed, A., Farag, A.: A new formulation for shape from shading for non-Lambertian surfaces. In: Proc. 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 17–22. IEEE Computer Society Press, New York (2006)
Vogel, O., Breuß, M., Weickert, J.: Perspective shape from shading with non-Lambertian reflectance. In: Rigoll, G. (ed.) DAGM 2008. LNCS, vol. 5096, pp. 517–526. Springer, Heidelberg (2008)
Oren, M., Nayar, S.: Generalization of the Lambertian model and implications for machine vision. International Journal of Computer Vision 14(3), 227–251 (1995)
Foley, J., van Dam, A., Feiner, S., Hughes, J.: Computer Graphics: Principles and Practice. Addison-Wesley, Reading (1996)
Harrison, V.G.W.: Definition and Measurement of Gloss. Printing & Allied Trades Research Association, PATRA (1945)
Smith, W.A.P., Hancock, E.R.: Facial shape-from-shading and recognition using principal geodesic analysis and robust statistics. International Journal of Computer Vision 76(1), 71–93 (2008)
Zhang, L., Dugas-Phocion, G., Samson, J.S., Seitz, S.M.: Single view modeling of free-form scenes. Journal of Visualization and Computer Animation 13(4), 225–235 (2002)
Chan, T., Vese, L.: Active contours without edges. IEEE Transactions on Image Processing 10(2), 266–277 (2001)
Caselles, V., Kimmel, R., Sapiro, G.: Geodesic active contours. International Journal of Computer Vision 22, 61–79 (1997)
Kichenassamy, S., Kumar, A., Olver, P., Tannenbaum, A., Yezzi, A.: Conformal curvature flows: from phase transitions to active vision. Archive for Rational Mechanics and Analysis 134, 275–301 (1996)
Sauvola, J., Pietikainen, M.: Adaptive document image binarization. Pattern Recognition 33(2), 225–236 (2000)
Weickert, J., Welk, M.: Tensor field interpolation with PDEs. In: Weickert, J., Hagen, H. (eds.) Visualization and Processing of Tensor Fields, pp. 315–325. Springer, Berlin (2006)
Prados, E., Camilli, F., Faugeras, O.: A unifying and rigorous shape from shading method adapted to realistic data and applications. Journal of Mathematical Imaging and Vision 25(3), 307–328 (2006)
Tschumperlé, D., Deriche, R.: Vector-valued image regularization with PDEs: A common framework for different applications. In: Proc. 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 651–656. IEEE Computer Society Press, Madison (2003)
Jin, H., Cremers, D., Wang, D., Yezzi, A., Prados, E., Soatto, S.: 3-d reconstruction of shaded objects from multiple images under unknown illumination. International Journal of Computer Vision 76(3), 245–256 (2008)
Perona, P., Malik, J.: Scale space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence 12, 629–639 (1990)
Weickert, J.: Theoretical foundations of anisotropic diffusion in image processing. Computing Supplement 11, 221–236 (1996)
Breuß, M., Vogel, O., Weickert, J.: Efficient numerical techniques for perspective shape from shading. In: Algoritmy, Podbanske, Slovakia, March 2009, pp. 11–20 (2009)
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Vogel, O., Valgaerts, L., Breuß, M., Weickert, J. (2009). Making Shape from Shading Work for Real-World Images. In: Denzler, J., Notni, G., Süße, H. (eds) Pattern Recognition. DAGM 2009. Lecture Notes in Computer Science, vol 5748. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03798-6_20
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DOI: https://doi.org/10.1007/978-3-642-03798-6_20
Publisher Name: Springer, Berlin, Heidelberg
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