Face recognition using locality sparsity preserving projections
Ying Wen, Shicheng Yang, Lili Hou, Hongda Zhang · 2016
In this paper, we present a new and effective dimensionality reduction method called locality sparsity preserving projections (LSPP). Locality preserving projections (LPP) and sparsity preserving projections (SPP) only focus on an aspect of local structure and sparse reconstructive information of the dataset, respectively. The proposed method integrates the sparse reconstructive information and local structure of data. The projection of LSPP is sought such that the sparse reconstructive weights and local preserving weights can be best preserved and integrated. Extensive experiments on ORL, Yale, Yale B, AR and CMU PIE face databases show the effectiveness of the proposed LSPP.