GPU-based fast scale invariant interest point detector

Hongtao Xie, Ke Gao, Yongdong Zhang, Jintao Li, Yizhi Liu
2010 2010 IEEE International Conference on Acoustics, Speech and Signal Processing  
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
more » ... r 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.
doi:10.1109/icassp.2010.5494898 dblp:conf/icassp/XieGZLL10 fatcat:qcttztzf4vabpkc6hwtiu42ek4