I’m a grad student in the Vision Science program at UC Berkeley. I’m a member of Bruno Olshausen‘s lab at the Redwood Center for Theoretical Neuroscience. I graduated in Fall 2005 from UC Davis with a degree in Computer Science.
In the future, I will put up research notes, reading lists, and research related software here.
One of my interests lies in natural scene statistics: see my quals reading list for a fairily thorough set of papers in this area.
For the time being, I will simply include an Ohloh widget of the tools I use for my scientific endeavors
See also
Python for Scientific Computing - a great list of resources put together by Fernando Perez.
Here’s my poster from the NVidia 2009 GPU Tech Conference:
Poster #19 - Ivanov, Paul
University of California, Berkeley (United States)
Estimating the Entropy of Natural Scenes from Nearest Neighbors using CUDA (local copy)
You can also see the rest of the posters from that conference.
There was recently an email on the VisionList requesting a mirror of the van Hateren image data set. Here are all of the .iml files, which form the set of linear images. There is another set of the same images in deblurred .imc files which corrected for the optics of the camera. Both sets can be downloaded in their entirety in two separate .tgz files here.
The original description of the dataset from Hans van Hateren’s site:
Still Images
The data below can be downloaded freely for scientific, non-commercial
uses. If you publish work based on these data, please cite the article
where this collection of images and its calibration are first described:
* van Hateren, J.H., van der Schaaf, A. (1998) Independent component
filters of natural images compared with simple cells in primary
visual cortex. Proc.R.Soc.Lond. B 265:359-366. Preprint version
21/11/97: postscript 3.3 Mb, compressed postscript 1.4 Mb, PDF 1.2
Mb, abstract, demo; reprint as published: PDF 0.4 Mb
Still image collection (approximately 4000 large calibrated images,
obtained with a Kodak DCS420 camera)
Philipp Lies maintains a mirror hosted at the Max Planck Institute for Biological Cybernetics, which contains a more complete description of the data, as well as both the linear .iml and the deblurred .imc files, as well as all of the information which was present at the original website (such as the file format and how to read files into matlab).