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I think the description is pretty accurate.

  1. For a given keypoint K1 from the first set (image), it takes every keypoint in the second set and calculates the distance. The keypoint K2 with the smallest distance will be considered its pair.

If you enable cross-checking, the pair is accepted only if K1 is the closest to K2 from the first set.

  1. Yes, NORM_L2 is the euclidean distance (=sum(da²)). The NORM_L1 is the sum of the distances on each dimension (=sum(abs(da))).

I think the description is pretty accurate.

  1. 1. For a given keypoint K1 from the first set (image), it takes every keypoint in the second set and calculates the distance. The keypoint K2 with the smallest distance will be considered its pair.

If you enable cross-checking, the pair is accepted only if K1 is the closest to K2 from the first set.

  1. 2. Yes, NORM_L2 is the euclidean distance (=sum(da²)). The NORM_L1 is the sum of the distances on each dimension (=sum(abs(da))).