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How did you decide on x,y and velocity of ball to predict bounces? #11
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@nyck33 Hey, thanks for opening the issue! Yep, predicting bounces sure took us a while. 186 x = int(circles[0][0][0])
187 y = int(circles[0][0][1]) We tried different methods:
That's generally all the methods we have tried. If there is anything else you would like to know, let us know! |
I tried a Kalman filter using that first plot you have up but that led nowhere. Over 80% is already pretty impressive but thanks for the clarification. |
@shukkkur This guy https://github.com/taikoma predicted bounce location using SVM and I believe it was trajectory. He had a blog post on https://qiita.com/ (in Japanese) which I was looking for and can't find anymore. |
@shukkkur have you seen this: https://arxiv.org/abs/2008.04524 |
No, I haven't. Thank you for sharing. Will make sure to have a look at it. |
I am not good at ML either, just an intern that doesn't understand half of what he does) |
To predict bounce points machine learning library for time series sktime was used. Specifically, TimeSeriesForestClassifier was trained on 3 variables: x, y coordinates of the ball and V for velocity (V2-V1/t2-t1).
Additional context
Add any other context or screenshots about the feature request here.
I want to try to improve the predictive accuracy but don't want to reinvent the wheel if you can share some info on what you tried and how you decided on these three factors.
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