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To take full advantage of the powerful computing capability of graphics processing units (GPU) to speed up local feature detection, we present a novel GPU-based scale invariant interest point detector, coined Harris-Hessian(H-H). H-H detects Harris points in low scale and refines their location and scale in higher scale-space with the determinant of Hessian matrix. Compared to the existing methods, H-H significantly reduces the pixel-level computation complexity and has better parallelism. Thedoi:10.1109/icassp.2010.5494898 dblp:conf/icassp/XieGZLL10 fatcat:qcttztzf4vabpkc6hwtiu42ek4