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

Second-order Anisotropic Gaussian Directional Derivative Filters for Blob Detection