I was looking for some commonly used approaches in computer vision to find the following calibration stickers and I was pretty surprised that I have not found any. I am not sure if I am just googling wrong terms or whether no one cares about this topic.

So I am wondering what is the common approach to find these pasterns ? Is it just by looking for geometrical objects of known properties combined with filtering of colors or by using some feature extractor such as SIFT (which I have not tried yet, but I think that the pattern is too simple for featrue extractor such as SIFT) or is there some more complex/robust approach?

Sorry for such a bad question, but I really did not find any discussions on that topic.

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  • $\begingroup$ Try using hough transform for detecting circles and generalised hough transform for detecting triangles.I think as preprocessing step first detect the object based on colour of wall and object. $\endgroup$ – Vinith Jun 22 '18 at 14:24

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