I still have many question marks flying around my head. There may be some miss-understanding that make my implementation is weak for scaling & orientation invariance (which should be the strongest compared with the other algorithms).
Ref :
My code is heavily base on Rob Hess`s implementation. But I don`t want to install opencv and can`t understand the descriptor building function. So I just sampling a rotated grid with fixed size in all scale. In the matching step, check distance between 2 descriptor only (accepted if d is less than 0.001)20100223
Get better result after pre-smoothing.
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