Face recognition based on dynamically determining neighborhood parameter of locally linear embedding algorithm.

In order to enhance the feature classification performance of localy linear embedding (LLE) algorithm for face recognition, the paper introduced minimum spanning tree algorithm and proposed a new local linear embedding algorithm with the dynamically determining neighborhood parameter. The new algorithm could automatically determine the neighborhood of the data point by using the single-chain clustering and further optimization algorithm, improved the insufficient of local linear embedding algorithm fixed neighborhood, as well as deal with the reality of non-uniform failures of source datasets. It used the improved algorithm and support vector machine (SVM) classifier for face recognition to get a higher upgrade of the average recognition rate on the ORL and YALB face database. And the simulation result shows the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]