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Figure 1: OpenCV can be used to apply augmented reality to real-time video streams. The very reason the OpenCV library exists is to facilitate real-time image processing. The library accepts input images/frames, processes them as quickly as possible, and then returns the results.
Implementing augmented reality with OpenCV We are now ready to implement augmented reality with OpenCV! Lines 2-6 handle importing our required Python packages. We'll use NumPy for numerical processing, argparse for parsing command line arguments, and imutils for basic image operations (such as resizing).
EasyAR. Easy AR is an AR SDK that can be used to develop AR apps and games across various platforms such as Android, iOS, windows, and more. It can also be used for Smartglasses. It is available across two-tier pricing packages that are equipped with enhanced APIs and increased compatibility.
Since AR applications often run on mobile devices, you could consider also other features detector/descriptor:
Generally if you can chose the markers you first detect a square target using an edge detector and then either Hough or simply contours - then identify the particular marker from the internal design. Rather than using a general point matcher.
Take a look at Aruco for well written example code.
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