Back in 1987 I wrote some code for generating ‘noisy objects’. I cleaned up that code over the years, enhanced some calculations, played with new Mathematica features. Now I’ve got stuff that looks like this. I’ll put a… Read More
Here’s Phillips, Mazzarella & Docter (2014) for VSS. Get the PDF here Phillips2014 (Draft of 13 May). Specularity and shape from line drawings. If you’re in Florida next week drop in and say ‘hi’. Or not. An interesting thought: this could… Read More
It never ends. Depth maps.
A friend of mine asked me a question about the way that standing waves make sand on a 2D plate make pretty patterns. So, I whipped up a quick 1D example in Mathematica. I threw 50 randomly distributed… Read More
More analysis from Dave Jacobs’ eye tracking project. We wrote all the analysis code ourselves in Mathematica. There’s a bug in the heat map compositing, but I shall procrastinate a solution soon. Lifted largely from Eye Tracking: A comprehensive… Read More
Eye tracking recurrence ala Anderson et al. 2013. With Dave Jacobs and the amazing Yarbus and Babcock software packages.
Curvature field calculations for a random noisy shape. Colors represent magnitude of curvature. Iso-contours also shown in lovely pink.
Hairy elongated noisy stimulus. The lines are surface normals, sampled across the object. They are generated using a continuous random method (sometimes called ‘noise’) and were used to test symmetry perception in 3D shape. … Read More
A stimulus, # 13, otherwise known as ‘golden boy’ Colors indicate mapping of under- and over-sculpt from a shape production experiment where we had artists and non-artists reproduce shapes using only vision, touch, or some combination of both… Read More
Statistical distribution of shape on a 3D object. A bell pepper from Norman et al. Each color represents a class of shape ala Koenderink’s “Shape Index”. The histogram below shows the distribution along with a key to the… Read More