A day of problem solving pictures.
One of the things I love about using Mathematica is that it helps me better understand the nature of my programming and problem solving. It’s a great tool to help make sense of problems, see your errors, verify… Read More
More good bad results
Some days, things don’t go well, but you end up with interesting looking things anyway.
NewGlaven
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
Vision Science 2014 poster
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
VSS Analysis Continues
It never ends. Depth maps.
Slippy slidy particles
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
Recurrence, heat maps, trajectories and fixations
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
Recurrence plot
Eye tracking recurrence ala Anderson et al. 2013. With Dave Jacobs and the amazing Yarbus and Babcock software packages.
Curvature Field Computations
Curvature field calculations for a random noisy shape. Colors represent magnitude of curvature. Iso-contours also shown in lovely pink.
Hairy Glaven
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