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Research on Face Recognition Method based on Cognitive Mechanism

机译:基于认知机制的人脸识别方法研究

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A face recognition method similar to human cognitive mechanism has been proposed. Motivated by the continuity rule of a same class samples, face recognition can be regarded as face pattern cognition. Compared with traditional statistical pattern based face recognition, it has a kind of relationship with human's cognitive mechanism. When face coverage of different people overlap, a person's face distribution in low dimension space has a certain kind of cohesion. With the increase of space dimension, the cohesion of a same class samples decreases, meanwhile the repellency of different class samples increases. However, with further increasing of dimension, both the cohesion of a same class and the repellency of different class decrease. The coverage of candidate face recognition is processed in a certain space. If it belongs to several candidate face coverage, Fisher LDA method can be applied to obtain the final results. Experiments based on ORL have proved that untrained random objects can be recognized perfectly.
机译:已经提出了类似于人类认知机制的面部识别方法。出于同一类别样本的连续性规则的激励,人脸识别可以被视为人脸模式识别。与传统的基于统计模式的人脸识别相比,它与人的认知机制具有某种关系。当不同人的面部覆盖重叠时,低维空间中人的面部分布具有某种凝聚力。随着空间尺寸的增加,相同类别的样本的内聚力降低,而不同类别的样本的排斥性增加。然而,随着尺寸的进一步增加,相同类别的内聚力和不同类别的排斥性均降低。候选面部识别的覆盖范围是在特定空间中处理的。如果它属于多个候选人脸覆盖,则可以应用Fisher LDA方法获得最终结果。基于ORL的实验证明,可以很好地识别未经训练的随机对象。

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