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Improving marksmanship with smooth kernel distribution

Posted 10 years ago
POSTED BY: Diego Zviovich
8 Replies
Posted 10 years ago
POSTED BY: Diego Zviovich
POSTED BY: Sjoerd Smit

enter image description here - another post of yours has been selected for the Staff Picks group, congratulations !

We are happy to see you at the tops of the "Featured Contributor" board. Thank you for your wonderful contributions, and please keep them coming!

POSTED BY: EDITORIAL BOARD

Nice post! Instead of finding Mean you could try local maxima. Also there are many ways of overlapping images, like ImageMultiply or Overlay.

tutorial = Import["https://wolfr.am/cEj2VscY"];
heatmap = Import["https://wolfr.am/cEj0rqGj"];
cropT = ImageResize[ImageTake[tutorial, {100, 765}, {1, 665}], 600];
cropH = ImageReflect[ImageResize[ImageTake[heatmap, {10, 550}, {25, 570}], 610], Left -> Right];
ImageMultiply[cropH, cropT]

enter image description here

POSTED BY: Vitaliy Kaurov

Because of Diego's self-proclaimed left-handedness we have to reflect the density plot accordingly. Or come up with a left handed version of the shooting-diagnosis breakdown stencil.

POSTED BY: Anton Antonov

True! I did not notice his lefty comment. I corrected with ImageReflect, thanks.

POSTED BY: Vitaliy Kaurov

I still have a lot to learn... Awesome work!

Really interesting -- thanks for sharing!

Do you have timestamps associated with the shooting images? It would be interesting to do temporal-spatial mining of shooting performance.

Another set of data and questions come from the idea to cross-correlate with the traffic landscapes while driving to the shooting range.

POSTED BY: Anton Antonov
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