Research on the Optimization of Locality Preserving Projections
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摘要: 保局投影算法的基础是构造一个模拟图像局部结构的最近相邻图,但该最近相邻图并不总能够准确表示图像的流形结构,该文提出了一种基于保局投影的迭代保局投影优化算法。该方法可以不断地迭代更新保局投影算法的最近相邻图,最近邻图的构成直接影响到保局投影算法的性能,因此,优化后的最近相邻图可以更好地表示出图像的流形结构。从而可以得到更佳的降维映射。对该算法与PCA及LPP的图像检索效果进行实验比较,结果表明,该算法可以获得更好的效果。Abstract: Locality Preserving Projections (LPP) is based on a nearest neighbor graph which models the local geometrical structure of the image manifold. However, this graph can not always accurately estimate the intrinsic manifold structure. A novel algorithm called Iterative locality preserving projections (ILPP) is preposed. ILPP iteratively updates the nearest neighbor graph, so that it can better model the intrinsic manifold structure. Experimental results comparison show that our algorithm outperforms PCA and LPP for image retrieval.
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