基于编码复杂度的混合结构稀疏人脸识别方法

模式识别与人工智能, 2015.

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Abstract:

利用编码复杂度表示数据的结构稀疏度,通过降低编码复杂度实现结构稀疏.在稀疏表示分类模型的基础上,通过聚类排序的方法构造结构化字典,形成混合结构稀疏模型.此模型结合类间样本的定长组结构与类内样本的动态可重叠组结构,以及误差的标准稀疏结构.为实现混合结构稀疏重构,提出改进的混合结构贪婪算法.实验表明对数据字典进行聚类排序可有效改进人脸的识别性能,在相同条件下,混合结构的性能优于其他结构,文中算法也优于其他算法.

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ZH基于编码复杂度的混合结构稀疏人脸识别方法
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