Jiang, Richard M. and Crookes, Danny and Luo, Nie (2010) Face Recognition in Global Harmonic Subspace. IEEE Transactions on Information Forensics and Security, 5 (3). pp. 416-424. ISSN 1556-6013
Full text not available from this repository.Abstract
In this paper, a novel pattern recognition scheme, global harmonic subspace analysis (GHSA), is developed for face recognition. In the proposed scheme, global harmonic features are extracted at the semantic scale to capture the 2-D semantic spatial structures of a face image. Laplacian Eigenmap is applied to discriminate faces in their global harmonic subspace. Experimental results on the Yale and PIE face databases show that the proposed GHSA scheme achieves an improvement in face recognition accuracy when compared with conventional subspace approaches, and a further investigation shows that the proposed GHSA scheme has impressive robustness to noise.