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