Automatic prediction of interest point stability
Many computer vision applications depend on interest point detectors as a primary means of dimensionality reduction. While many experiments have been done measuring the repeatability of selective attention algorithms [MTS+05, BL02, CJ02, MP07, SMBI98], we are not aware of any method for predicting the repeatability of an individual interest point at runtime. In this work, we attempt to predict the individual repeatability of a set of 106 interest points produced by Lowe's SIFT algorithm [Low03], Mikolajczyk's Harris-Affine [Mik02], and Mikolajczyk and Schmid's Hessian-Affine [MS04]. These ...
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