Bivariate Feature Localization for SIFT Assuming a Gaussian Feature Shape

@inproceedings{Cordes2010BivariateFL,
  title={Bivariate Feature Localization for SIFT Assuming a Gaussian Feature Shape},
  author={Kai Cordes and Oliver M{\"u}ller and Bodo Rosenhahn and J{\"o}rn Ostermann},
  booktitle={ISVC},
  year={2010}
}
In this paper, the well-known SIFT detector is extended with a bivariate feature localization. This is done by using function models that assume a Gaussian feature shape for the detected features. As function models we propose (a) a bivariate Gaussian and (b) a Difference of Gaussians. The proposed detector has all properties of SIFT, but provides invariance to affine transformations and blurring. It shows superior performance for strong viewpoint changes compared to the original SIFT. Compared… CONTINUE READING