The matlab code for computing optimal optical flow masks for compression is avaible here. Note that the code is hardly documented and provided “as-is”. The code is released under a GPL v3 licence (unless specified differently).
Recently I acquired a Raspberry Pi 4 and decided to build a tiny computer cluster out of it. The goal is to do play around a bit with parallel computing technology.
Besides my research in computer vision related tasks such as optical flow, photometric stereo, and shape matching and my focus on PDE-based compression, I have also ventured in other image processing tasks.
I have used machine learning techniques in various projects. Our most successful applications were in the context of quantizing colour values for optimized inpainting and in accoustic source characterizations.
Source Code The source code for clustering methods used for quantizing optimal masks can be found here.
Over the years I have written quite a lot of Matlab code. The code is available here, here, here, and here and covers mostly image processing and interpolation/approximation topics. All the code is released under a GPL v3 licence (unless specified differently).
Over the years I have written quite a lot of Mathematica code. The code is available here and here and covers mostly image processing topics. All the code is released under a GPL v3 licence (unless specified differently).
Floating point computations on computers may behave differently than one might expect. Every software developer should be aware of these since computed results may be off by orders of magnitude in the worst case.