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Unread 15-10-2014, 23:37
Jared Russell's Avatar
Jared Russell Jared Russell is offline
Taking a year (mostly) off
FRC #0254 (The Cheesy Poofs), FRC #0341 (Miss Daisy)
Team Role: Engineer
 
Join Date: Nov 2002
Rookie Year: 2001
Location: San Francisco, CA
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Re: Optimal board for vision processing

Quote:
Originally Posted by techhelpbb View Post
I also spent part of each competition chasing around teams sending video back to the driver's station in ways that messed with the field at the request of the FTA. Very competent people were having issues with this so I do not think it is quite so cut and dry. If anyone wanted I could toss that data together for the events at which I volunteered in MAR.
In 2012-2013, 341 competed at 9 official events and numerous other offseason competitions. We never had any issues with streaming video. There were a handful of matches where things didn't work, but they all traced back to user error or an early match start (before our SmartDashboard had connected).

I believe that when people have trouble with this setup, it can usually be traced back to choosing camera settings poorly. Crank the exposure time down along with brightness, raise contrast, and you will find that images are almost entirely black except for your vision target (if necessary, provide more photons from additional LED rings to improve your signal to noise ratio). A mostly-black image with only your target illuminated is advantageous for a bunch of reasons:

1) JPEG compression can be REALLY effective, and each image will be ~20-40KB, even at 640x480. Large patches of uniform color are what JPEG loves best.

2) Your detection algorithm has far fewer false alarms since most of the background is simply black.

3) You can get away with conservative HSL/HSV/RGB thresholds, so you are more robust to changes in field lighting conditions. We won 6 of those 9 on-season competitions (and more than half of the offseasons) using 100% camera driven auto-aim, and never once touched our vision system parameters other than extrinsic calibration (ex. if the camera got bumped or our shooter was repaired).

In my experience, I find that the vast majority of teams don't provide enough photons and/or don't crank down their exposure time aggressively enough. Also, I strongly suspect (but do not know for sure) that the Bayer pattern on the Axis camera effectively makes it twice as sensitive to green light, so you might find that green LEDs work much better than other colors. We used green LEDs both years.

It is also possible that if your vision processing code falls behind, your laptop will get sluggish and bad things will happen. Tune your code (+ camera settings, including resolution) until you can guarantee that you will process faster than you are acquiring.

Last edited by Jared Russell : 15-10-2014 at 23:39.