The `orthogonal algorithm´ for optical flow detection using dynamic programming

An algorithm for optical flow detection is introduced. It is based on an iterative search for a displacement field that minimizes the L ₁ or L₂ distance between two images. Both changes are sliced into parallel and overlapping strips. Corresponding strips are aligned using dynamic programming. Two passes are performed using orthogonal slicing directions. This process is iterated in a pyramidal fashion by reducing the spacing and width of the strips. This algorithm provides very-high-quality matching for calibrated patterns as well as for human visual sensation. The results appear to be at least as good as those obtained with classical optical flow detection methods