Our method outperforms other manifold based methods such as Nearest Manifold and other methods such as PCA, LDA Modular PCA, Generalized 2D PCA and super- ...

We propose a new method to model this higher dimensional manifold with available data, and use a reconstruction technique to approximate unavailable data points ...

Ann Theja Alex, Vijayan K. Asari, Alex Mathew: Neighborhood Dependent Approximation by Nonlinear Embedding for Face Recognition. ICIAP (1) 2011: 544-553.

Neighborhood preserving embedding (NPE) is a linear approximation to the locally linear embedding algorithm which can preserve the local neighborhood ...

Neighborhood dependent approximation by nonlinear embedding for face recognition. AT Alex, VK Asari, A Mathew. Image Analysis and Processing–ICIAP 2011, 544 ...

The NPCE automatically learns the local neighbourhood characteristic and discovers the compact linear subspace which optimally preserves the intrinsic manifold ...

Neighborhood Dependent Approximation by Nonlinear Embedding for Face Recognition ... Variations in pose, illumination and expression in faces make face ...

Missing: Dependent Approximation

In this paper, a discriminative manifold learning method for face recognition is proposed which achieved the discriminative embedding the high dimensional ...

In this Section, we investigate the use of NPE on face analy- sis (representation and recognition). ... non-smiling) and facial details (glasses or no glasses).