一种基于E-HMM的选择性集成人脸识别算法
doi: 10.3724/SP.J.1146.2007.01224
A Face Recognition Algorithm Based on Selective Ensemble of E-HMMs
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摘要: 基于嵌入式隐马尔可夫模型(Embedded Hidden Markov Model, E-HMM)的人脸识别方法的识别性能依赖于模型参数的合理选择。提出了一种基于E-HMM的多模型选择性集成人脸识别算法，选择出个体精度高且互补性强的模型来进行集成的人脸识别。实验结果表明，与传统的基于E-HMM的人脸识别方法相比，新算法不仅可以获得更好、更稳定的识别效果，而且具有更强的泛化能力。Abstract: The performance of Embedded Hidden Markov Model (E-HMM) based face recognition algorithm heavily depends on the selection of model parameters. A selective ensemble of multi E-HMMs based face recognition algorithm is proposed, selecting many accurate and diverse models for ensemble face recognition. Comparing with the traditional E-HMM based face recognition algorithm, the experimental results illustrate that the proposed method can not only obtain better and more stable recognition effect, but also achieve higher generalization ability.
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