Making shape from shading work for real-world images

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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. © 2009 Springer Berlin Heidelberg.

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APA

Vogel, O., Valgaerts, L., Breuß, M., & Weickert, J. (2009). Making shape from shading work for real-world images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5748 LNCS, pp. 191–200). https://doi.org/10.1007/978-3-642-03798-6_20

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