8 Apr 2010 motters   » (Master)

Whilst testing out omnidirectional stereo vision I thought it would be a good idea to try to apply a dense stereo method to images like the ones used to produce this anaglyph.

http://www.youtube.com/watch?v=3L-gJhATQOg

Here the disparity is vertical rather than horizontal as is usually the case for stereo cameras.

However, it became apparent that I don't yet have a dense stereo algorithm for v4l2stereo, so I decided to take some time out to develop one, with the hope being that whatever is developed in a conventional stereo vision setup can be similarly applied to the omnidirectional case.

The stereo correspondence method which I've used for dense stereo is a fairly conventional one, and I've made extensive use of openmp to make it as multi-core scalable as possible. This uses the simple "patch matching" approach which is commonly described in the literature, but works reasonably well on the Minoru provided that some initial correction is done to make the colour mean and variance in the left and right images as similar as possible, so that comparing pixels becomes a less haphazard affair.

An example of the end result is the "big blob detection" reminiscent of what I had running on the Rodney humanoid over five years ago appears in the following video.

http://www.youtube.com/watch?v=ZKnWJTOzyk4

The depth resolution isn't fantastic, but it's functional and may be of use for obstacle detection or just detecting people nearby.

Also I wanted to experiment with integrating this code with the Willow Garage ROS system. This would potentially enable very expensive stereo cameras traditionally used in academic research to be replaced by something like a Minoru webcam, or a pair of webcams, which would be affordable to the hobbyist. The current source code release for v4l2stereo includes example ROS publisher and subscriber, which should make integration with ROS based robots into a fairly straightforward process.

http://code.google.com/p/sentience/wiki/MinoruWebcam

http://code.google.com/p/libv4l2cam/

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