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Asked: 2026-05-15T02:38:11+00:00

I’m trying to write a simple tracking routine to track some points on a

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I’m trying to write a simple tracking routine to track some points on a movie.

Essentially I have a series of 100-frames-long movies, showing some bright spots on dark background.
I have ~100-150 spots per frame, and they move over the course of the movie. I would like to track them, so I’m looking for some efficient (but possibly not overkilling to implement) routine to do that.

A few more infos:

  • the spots are a few (es. 5×5) pixels in size
  • the movement are not big. A spot generally does not move more than 5-10 pixels from its original position. The movements are generally smooth.
  • the “shape” of these spots is generally fixed, they don’t grow or shrink BUT they become less bright as the movie progresses.
  • the spots don’t move in a particular direction. They can move right and then left and then right again
  • the user will select a region around each spot and then this region will be tracked, so I do not need to automatically find the points.

As the videos are b/w, I though I should rely on brigthness. For instance I thought I could move around the region and calculate the correlation of the region’s area in the previous frame with that in the various positions in the next frame. I understand that this is a quite naïve solution, but do you think it may work? Does anyone know specific algorithms that do this? It doesn’t need to be superfast, as long as it is accurate I’m happy.

Thank you

nico

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1 Answer

  1. Editorial Team

    I would suggest the Pearson’s product. Having a model (which could be any template image), you can measure the correlation of the template with any section of the frame.

    The result is a probability factor which determine the correlation of the samples with the template one. It is especially applicable to 2D cases.
    It has the advantage to be independent from the sample absolute value, since the result is dependent on the covariance related with the mean of the samples.

    Once you detect an high probability, you can track the successive frames in the neightboor of the original position, and select the best correlation factor.

    However, the size and the rotation of the template matter, but this is not the case as I can understand. You can customize the detection with any shape since the template image could represent any configuration.

    Here is a single pass algorithm implementation , that I’ve used and works correctly.

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