Improved neighborhood preserving embedding approach

Ruicong Zhi; Qiuqi Ruan

doi:10.1117/12.747709

15 November 2007 Improved neighborhood preserving embedding approach

Ruicong Zhi, Qiuqi Ruan

Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 67880O (2007) https://doi.org/10.1117/12.747709
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

In this paper, we proposed a manifold-based algorithm called Orthogonal Neighborhood Preserving Embedding (ONPE) for dimensionality reduction and feature extraction. ONPE algorithm is based on the Neighborhood Preserving Embedding (NPE) algorithm. NPE is an unsupervised dimensionality reduction method which is the linear approximation of classical nonlinear method. However, the feature vectors obtained by NPE are nonorthogonal. ONPE inherits NPE's neighborhood preserving property and produces orthogonal feature vectors. As orthogonal eigenvectors preserve the metric structure of the image space, the ONPE algorithm has more neighborhood preserving power and discriminating power than NPE. Furthermore, ONPE can find the mapping which best preserves the manifold's estimated intrinsic geometry structure in a linear sense. Experimental results show that ONPE is an effective method for feature extraction.

Citation Download Citation

Ruicong Zhi and Qiuqi Ruan "Improved neighborhood preserving embedding approach", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67880O (15 November 2007); https://doi.org/10.1117/12.747709

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KEYWORDS

Principal component analysis

Detection and tracking algorithms

Databases

Facial recognition systems

Feature extraction

Pattern recognition

Reconstruction algorithms

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