Scaling Laws in Natural Scenes and the Inference of 3D Shape

Lee, Tai-sing, Potetz, Brian R.

Neural Information Processing Systems 

This paper explores the statistical relationship between natural images and their underlying range (depth) images. We look at how this relationship changesover scale, and how this information can be used to enhance low resolution range data using a full resolution intensity image. Based on our findings, we propose an extension to an existing technique known as shape recipes [3], and the success of the two methods are compared using images and laser scans of real scenes. Our extension is shown to provide a twofold improvement over the current method. Furthermore, wedemonstrate that ideal linear shape-from-shading filters, when learned from natural scenes, may derive even more strength from shadow cues than from the traditional linear-Lambertian shading cues.

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