HSR: L1/2 Regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection

23 Sep 2014 Bo Han Bo He Tingting Sun Mengmeng Ma Amaury Lendasse

In this paper, we propose a novel method for fast face recognition called L1/2 Regularized Sparse Representation using Hierarchical Feature Selection (HSR). By employing hierarchical feature selection, we can compress the scale and dimension of global dictionary, which directly contributes to the decrease of computational cost in sparse representation that our approach is strongly rooted in... (read more)

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