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Originally Posted by Uberbots
Ive looked through this a bit and basically conceptualized a couple of ways to go about this. First off... if you look at kevin's old camera code you will see that all of the data that you could ever need it within the t_packet_data structure. The bounding box corners are there, along with the centroid location.
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Yes, it's true! Thanks for noticing.
Quote:
Originally Posted by Uberbots
the way that i am conceptualizing going about this is pretty much to use size and confidence in order to determine the number of targets. the way i see it, the confidence will decrease when you have a low amount of tracked pixels within a large bounding box. When this confidence goes below a certain threshold, the code will know that only one target is in sight. The next challenge is finding the centroid of each target.
Ok, you know that the camera's X boundaries (but not necessarily the y boundaries) will mark the left edge of the left target, and the right edge of the right target. you will not know the height from this data, but you will not need to. the targets are in a fixed aspect ratio (like 2:1 w:h i believe), and you know the tracked pixels that you have. With this data, by dividing the tracked pixels by two and conforming each dividend to the aspect ratio, you can get an approximate X location of each target.
if you combine this method with the frame differencing data you could probably get the approximate Y value of each target as well. I will have to play around with this method a bit more in labView before i am able to come up with a conclusive algorithm... but that is what i have for now.
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Excellent analysis. Another bit of data you can use is the location of the centroid within the bounding rectangle. The centroid will be closer to the side of the rectangle with the nearest green light.
-Kevin