An Improved Block 2DPCA Face Recognition Algorithm with L1-Norm

Hao Zheng; Lei Pan

doi:10.4028/www.scientific.net/AMR.457-458.1077

Paper Titles

PSTree-Based Multi-Resolution Model for Buildings Simplification
p.1056

Numerical Simulation of Fluid-Structure Interaction for Tension Membrane Structures
p.1062

Analysis on Organization Networking Logistics Enterprises and Service Value Creation
p.1066

A New Approach to Fault Diagnosis for Satellite Control Systems Based on Machine Learning
p.1070

An Improved Block 2DPCA Face Recognition Algorithm with L1-Norm
p.1077

An Adaptive Clustering and Inter-Cluster Negotiation Protocol for Multi-Target Tracking Based on WSN
p.1083

Non-Autonomous Wheeled Mobile Robot Trajectory Tracking Control Based on the Navigation via WSN
p.1089

Research on the Bearing Capacity of Unsupported Random Launching Site
p.1096

Improve the Dyeing Property of Cotton Fabric via Corona Discharge
p.1101

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 457-458An Improved Block 2DPCA Face Recognition Algorithm...

An Improved Block 2DPCA Face Recognition Algorithm with L1-Norm

Abstract:

Most of the existing Block 2DPCA algorithms are based on Frobenius norm, which makes them sensitive to outliers. In this paper, we propose a new improved Block 2DPCA algorithm with L1-norm, which is robust to outliers. The experimental results of FERET face database indicated that the recognition performance of new algorithm is superior to Block 2DPCA, more robust than Block 2DPCA.