Abstract
We propose a method for rapidly classifying surface reflectance directly from the output of spatio-temporal filters applied to an image sequence of rotating objects. Using image data from only a single frame, we compute histograms of image velocities and classify these as being generated by a specular or a diffusely reflecting object. Exploiting characteristics of material-specific image velocities we show that our classification approach can predict the reflectance of novel 3D objects, as well as human perception.
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Doerschner, K., Kersten, D., Schrater, P. (2009). Rapid Classification of Surface Reflectance from Image Velocities. In: Jiang, X., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2009. Lecture Notes in Computer Science, vol 5702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03767-2_104
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DOI: https://doi.org/10.1007/978-3-642-03767-2_104
Publisher Name: Springer, Berlin, Heidelberg
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