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. Key words: specular flow, rapid surface reflectance classification, velocity histogram, material perception, spatio-temporal filtering
Katja Doerschner, Daniel Kersten, Paul R. Schrater