  Interest point detection methods have received increasing attention and are
widely used in computer vision tasks such as image retrieval and 3D
reconstruction. In this work, second-order anisotropic Gaussian directional
derivative filters with multiple scales are used to smooth the input image and
a novel blob detection method is proposed. Extensive experiments demonstrate
the superiority of our proposed method over state-of-the-art benchmarks in
terms of detection performance and robustness to affine transformations.
