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Computer Vision Applications and Linux?
blackcoot asks: "I'm about to start work on a summer project with my advisor, part of which involves getting a lab set up for real time (or as close as we can get) computer vision applications. Currently, the only machines in the lab with digital video cameras attached to them are Win2k boxen, and that's only because we haven't been able to find reasonable drivers for the firewire cameras that we have. My advisor and I would much rather *not* write our own driver for these cameras; right now my advisor has the budget for a couple reasonably inexpensive cameras. This leads me to a couple questions: are there firewire (or equivalently high bandwidth bus) based digital video cameras (not framegrabbbers) out there that have reasonably solid Linux or Video4Linux drivers; have any Slashdot readers tried to build a vision type application under Linux (something that does more processing than Xaw TV); Am I setting myself up for a whole world of pain trying to make this happen under Linux, or is it doable? Any words of wisdom? Your help is much appreciated."
If this is strictly a summer project (for you) and you have very little computer vision experience, I recommend spending your time learing basic computer vision algorithms/processes. They are pretty much the same from platform to platform. Regardless of the OS, get a student copy of Matlab and the Image Processing Toolkit. It won't do real time stuff, but it makes algorithm development and experimentation REALLY easy. Once everything has been fleshed out, convert to C,C++. It sounds like you are building a generic rig for a variety of experiments. For real time vision, a framegrabber is recommended. This combo might be a bit more expensive up front, but the framegrabber software will get you up and running more quickly than having to write your own driver. (I doubt you will learn much computer vision writing device drivers.)The Mutech MV-1000 has decent linux support, and does not cost too much. ($1500?) Look at Matrox too. Other practical things to consider: The "linux comfort level" of people who will be taking over your project in the fall, interchangable lenses, GOOD lighting (very often overlooked), color or grayscale, quality of images/data. I'm working on a stereo vision system for autonomous mapping/navigation. I do much of my initial algorithm development in linux/Matlab using images from 2 defective USB webcams. Once the rest of the $$$ comes in, almost everything will be converted to C under win2k/matrox. The non real-time stuff, like camera calibration, and NN training will remain Matlab. Summary: If you are planning on doing a lot of computer vision stuff, go ahead and spend time playing with your hardware/software options. If this is a 3-4 month fling, start writing/playing with computer vision routines as soon as possible.