Abstract
A novel Hierarchical Structured Dictionary Learning (HSDL) algorithm is proposed in this paper. It aims to learn classs-pecific dictionaries for all classes simultaneously in a hierarchical structure. A discriminative term based on Fisher discrimination criterion is jointly considered for both the classs-pecific dictionaries in the lower level and the shared dictionaries in the upper level to enhance the discrimination of dictionaries. The experimental results evaluated on the ImageNet database have shown the superior performance of HSDL over the state-of-the-art dictionary learning methods.