Discriminant sparse local spline embedding with application to face recognition

In this paper, an efficient feature extraction algorithm called discriminant sparse local spline embedding (D-SLSE) is proposed for face recognition. A sparse neighborhood graph of the input data is firstly constructed based on a sparse representation framework, and then the low-dimensional embedding of the data is obtained by faithfully preserving the intrinsic geometry of the data samples based on such sparse neighborhood graph and best holding the discriminant power based on the class information of the input data. Finally, an orthogonalization procedure is perfomred to improve discriminant power. The experimental results on the two face image databases demonstrate that D-SLSE is effective for face recognition.