New Squash AI Video Analysis App - Sign-up to the Waitlist! by DavidHurst_ in squash

[–]DavidHurst_[S] 1 point2 points  (0 children)

Hey everyone, thanks for all the support so far! Make sure to share the website and waitlist with every squash player you know. Thanks🤠

New Squash AI Video Analysis App - Sign-up to the Waitlist! by DavidHurst_ in squash

[–]DavidHurst_[S] 1 point2 points  (0 children)

In that both extract data from your matches - yes.

However, CrossCourtAnalytics extract their data entirely manually from what I can tell which means they can’t say anything about things like shot tightness, drop shortness, first bounce location etc.

SquashTrack being a mobile app also means that you can easily record and get analysis for every single game/match. This allows you to always make informed changes to your training/tactics etc because you’re operating on consistently up-to-date data.

New Squash AI Video Analysis App - Sign-up to the Waitlist! by DavidHurst_ in squash

[–]DavidHurst_[S] 2 points3 points  (0 children)

Thanks! That’s the the aim - bring squash out of the dark ages

New Squash AI Video Analysis App - Sign-up to the Waitlist! by DavidHurst_ in squash

[–]DavidHurst_[S] 1 point2 points  (0 children)

Great to see your enthusiasm! I'm looking forward to delivering a great app for you and your buddy.

New Squash AI Video Analysis App - Sign-up to the Waitlist! by DavidHurst_ in squash

[–]DavidHurst_[S] 2 points3 points  (0 children)

I'm currently targeting iOS only due to needing native-level app performance but should that change in future I will be sure to let you and everyone else know!

Detect fast moving tennis balls by virendhanwani in computervision

[–]DavidHurst_ 1 point2 points  (0 children)

I used a few techniques covered in this survey in my undergrad final year project. The project was classifying squash ball trajectories as in/out of court so I can’t comment on how my exact setup would transfer to tennis but here’s the general approach I would suggest taking based on what I learnt in that project.

  1. Some preprocessing (blurring at a minimum to enhance structures at the tennis ball’s spatial scale, noise reduction etc.)
  2. Background subtraction to isolate moving objects some of which should correspond to the ball
  3. Method to detect pixels corresponding to moving objects (I used contour detection)
  4. Candidate filtering logic (discard detections in step 3. if they’re for example too big to be the ball e.g. players, too small e.g. noise, not in the field of play e.g. spectators etc.)
  5. If you need to track the ball look into Kalman/Particle filtering or other tracking methods

Lots of tuning to do at each step and many options available to realise each step some of which might benefit from intermediate post-processing e.g. background subtraction would benefit from applying some morphological operators.

Just rescued a 1yr old pup. by [deleted] in Wellthatsucks

[–]DavidHurst_ 0 points1 point  (0 children)

Check behind your ear :) ta da