Locally Maintainning Projection of Typical Correlation Analysis
Year: 2013
Type: article
Abstract: According to the problem that conventional subspace linear analysis method can't describe the manifold structure of the sample accurately,based on the theory of canonical component analysis algorithm and locality preserving projections algorithm,we combine two kinds of algorithms. The article puts forward restricted-class locality preserving canonical component analysis algorithm. The algorithm distinguishes the sample information and keeps the local information structure of the sample by introducing the class information. The algorithm achieves the level of maximum related on the base of making a distinction of the sample class information. It as well as makes the feature projections have no relativity. This algorithm significantly improves the algorithm's recognition rate. The algorithm respectively does the experiment on the Yale face and AR face database. The recognition rate can reach to 98%.
Source: Harbin Ligong Daxue xuebao
Author: Weiyu Cheng
Institution: Harbin University of Science and Technology
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $581
OpenAlex ID: W2350683052