We propose a novel method for detecting scale-invariant keypoints. Our method first computes multiscale representations of an image for several different measures by scale-space filtering. Then we localize feature points in the image plane and determine the characteristic scales for these points using a saliency metric. Finally, some highly salient points are selected as keypoints. These points are invariant to scale and rotation. Experimental results show very satisfactory performance of the detector.