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FACE RECOGNITION USING ORTHOGONAL LOCALITY PRESERVING PROJECTIONS

机译:使用正交位置保存投影的人脸识别

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In this paper a hybrid technique is used for determining the face from an image. Face detection is one of the tedious job to achieve with very high accuracy. In this paper we proposed a method that combines two techniques that is Orthogonal Laplacianface (OLPP) and Particle Swarm Optimization (PSO). The formula for the OLPP relies on the Locality Preserving Projection (LPP) formula, which aims at finding a linear approximation to the Eigen functions of the astronomer Beltrami operator on the face manifold. However, LPP is non-orthogonal and this makes it difficult to reconstruct the information. When the set of features is found by the OLPP, with the help of the PSO, the grouping of the image features is done and the one with the best match from the database is given as the result. This hybrid technique gives a higher accuracy in less processing time.
机译:在本文中,使用混合技术来确定来自图像的面部。面部检测是以非常高的准确性实现的繁琐工作之一。在本文中,我们提出了一种结合两种正交Laplacianface(OLPP)和粒子群优化(PSO)的两种技术的方法。 OLPP的公式依赖于局部保留投影(LPP)公式,其目的在于对面歧管上的天文学家Beltrami操作员的eIGen函数找到线性近似。然而,LPP是非正交,这使得难以重建信息。当OLPP找到一组特征时,在PSO的帮助下,将完成图像特征的分组,并作为结果给出了与数据库最佳匹配的组。这种混合技术在更少的处理时间内提供更高的准确性。

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