1
$\begingroup$

I am trying to calculate the trajectory of a moving object (specifically, a thrown object) through a series of video frames. My tracking algorithm can reliably detect ~90% of the object occurrences throughout the video, giving an x, y, and radius size (in pixels) value. However, the tracking method is not resilient to noise and therefore a lot of false-positives are picked up too.

I was wondering if anyone could point me in the right direction to finding an algorithm that will help me to:

  • (1) Filter the noisy data from the found points
  • (2) build a good trajectory estimation using these filtered points and a simple physics model
  • (3) potentially even help to interpolate points within the trajectory that were missed by the tracking algorithm.

Any help would be greatly appreciated.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.