Robust and Fast Keypoint Recognition Based on SE-FAST

In this paper, we present a key point recognition scheme, which consists of a novel feature detector and an efficient descriptor. Inspired by FAST (features from accelerated segment test), our feature detector is easy to compute and has high repeatability. Scale-invariance and optimized robustness are gained by extending traditional FAST to scale space.We combine this detector with an adapted version of SURF (speed up robust features) descriptor, providing the system with all means to do feature matching and object detection. Experimental evaluation and comparison with standard SURF using Hessian matrix-based detector are included in this paper, showing improvement in speed with comparable robustness.