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Comment by hemangshah | Hacker News Reader

There are visual tracking techniques that are not only more stable and robust that meanshift, but can also handle occlusions, adapt to changes in appearance models, etc. Have a look at the VOT challenge[1] for the state-of-art in visual tracking.

[1] http://www.votchallenge.net/vot2014/download/vot_2014_paper....

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Thanks for the link, I'm aware of some of the methods cited. This first PoC was just to check how fast and how good Meanshift would work with that image quality. I'll try to implement some more robust approach, specially some method that could handle occlusions.

Out of interest, what kind of hardware specs does the box doing the image processing have (CPU speed, #cores, and memory in particular). Do you expect to be limited by the compute capabilities?

From what I gather, this was running on the drone itself, in real time.

#Edit. Scratch that, the code is opening a file "upabove.mp4"... i.e. not realtime, on the drone. Realtime on a PC/laptop.

You're correct, this is a post-processing operation, however I took care to do something that works in real time, so you can use this same algorithm for any FPV transmission, which is the next step that I'm planning to implement (but with more robust features).

Christian, please also be aware that some of the techniques do not incorporate changes in scale of the tracked object. If you are working with aerial footage then this might be an important consideration. I've recently worked on a similar problem, so you need any help, please feel free to email me (email address is given in my profile)

Thanks for the feedback ! I'm planning to use more robust and scale invariant features for this so this problem of different levels of zoom would be solved (at least to the limits of what can be done).

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