Shawn Lankton Online

Recently, I started looking at faster ways to perform dense stereo matching for some work with 3D video. After some experimentation, I found out that by using a selective mode filter paired with naive correspondence matching, I was able to get satisfactory results very quickly. Check out the slide show below for some results!

Here is a download-able Matlab demo, which should work on any pre-aligned stereo image pairs:

stereo_modefilt.zip

The entire code is written in Matlab/C++/MEX. The stereo matching is all in Matlab, and the selective mode filter is coded in C++ and callable from Matlab (meaning it must be compiled before it can run). Currently, the correspondence is the major bottleneck, so anyone who can improve this, please let me know! Enjoy.

2D is nice, but these days I’m getting interested in doing computer vision in 3D. One way to get 3D data is to use two cameras and determine distance by looking at the differences in the two pictures (just like eyes!). In this project I show some initial results and codes for computing disparity from stereo images.    Click to continue →