In this paper we show that filtered eigenspaces are also inherently robust w.r.t. (non-Gaussian) noise and occlusions. We argue that this robustness stems ...

In the recent literature, gradient-based (FlteredJ eigenspaces have been used as a means to achieve illu- mination insensitivity. In this papez we show that ...

In the recent literature, gradient-based (filtered) eigenspaces have been used as a means to achieve illu- mination insensitivity.

In this paper, we show that filtered eigenspaces are also inherently robust w.r.t. (non-Gaussian) noise and occlusions. We argue that this robustness stems ...

(2002). A Gradient-Based Eigenspace Approach to Dealing with Occlusions and Non-Gaussian Noise. In Proceedings - 16th ICPR (pp. 977-980). IEEE Computer Soc.. A ...

A Gradient-Based Eigenspace Approach to Dealing with Occlusions and Non-Gaussian Noise ICPR, 2002. ICPR v2 2002 · DBLP · Scholar · DOI. Full names. Links ISxN.

-Based Eigenspace Approach to Dealing with Occlusions and Non-Gaussian Noise ... In the recent literature, gradient-based (filtered) eigenspaces have been ...

Bibliographic details on A Gradient-Based Eigenspace Approach to Dealing with Occlusions and Non-Gaussian Noise.

A Gradient-Based Eigenspace Approach to Dealing with Occlusions and Non-Gaussian Noise. ... In the recent literature, gradient-based (filtered) eigenspaces ...

A gradient-based eigenspace approach to dealing with occlusions and non-Gaussian noise ... eigenspaces are also inherently robust w.r.t. (non-Gaussian) ...