Quote:
Originally Posted by SoftwareBug2.0
Something you can try is to multiply the score of each match by an estimate of how likely that result should be. For example, if you think the robot should be moving slowly, then results that would imply large motions should be penalized.
One way to do this is to use normal distributions. For example, you might estimate that you should have moved 10 px forward since the last frame with a standard deviation of 3. From That, you can give an initial estimate of how likely having moved 8 px is vs 10 px vs 1 px. So the initial estimate would say 10 px of movement is likely and 8 px is reasonable and 1 px is unlikely because it's 3 standard deviations away from what was expected.
I hope that makes sense.
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I hadn't tried that yet. Maybe instead of using a solid estimate, I could use the current speed as a base point, and from there it would reduce the score for shifts as they get father away from the avg shift. Actually wait no. That would probably screw up the accuracy. I'll just go with yours