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Semi-global matching (SGM) is among the top-ranked stereovision algorithms. SGM is an efficient strategy for approximately minimizing a global energy that comprises a pixel-wise matching cost and pair-wise smoothness terms. In SGM the two-dimensional smoothness constraint is approximated as the average of one-dimensional line optimization problems. The accuracy and speed of SGM are the main reasons for its widespread adoption, even when applied to generic problems beyond stereovision. Thisdoi:10.5244/c.29.90 dblp:conf/bmvc/FaccioloFM15 fatcat:zaarxnl4l5cdfeqxfuyyth37ia