1. Let H be the Hessian matrix of f at the point x. 2. Further the Hessian matrix of second derivatives will have both positive and negative eigenvalues. 3. SURF uses a blob detector based on the Hessian matrix to find points of interest. 4. The trace of Hessian matrix is identical to the Laplacian of Gaussians ( LoG ): 5. To calculate the quadratic approximation, one must first calculate its gradient and Hessian matrix . 6. The frequencies are related to the eigenvalues of the Hessian matrix , which contains second derivatives. 7. H _ F is the Hessian matrix of F ( matrix of the second derivatives ). 8. :: Check whether the Hessian matrix is positive definite at the singular point or not. 9. The different cases may be distinguished by considering the eigenvalues of the Hessian matrix of second derivatives. 10. Instead, the Hessian matrix is approximated using updates specified by gradient evaluations ( or approximate gradient evaluations ).
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