GPU-based fast scale invariant interest point detector
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. The experiment results show that with the assistance of GPU, H-H achieves up to a 10–20x speedup than CPU-based method. It only takes 6.3ms to detect a 640 × 480 image with high detection accuracy, meeting the need of real-time detection.