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Enhanced LBP-Based Face Recognition System Using a Heuristic Approach for Searching Weight Set

机译:基于启发式方法的基于LBP的增强型人脸识别系统搜索权重集

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Local Binary Patterns is one of the most effective approaches for pattern recognition in general and face recognition in particular. There have been many studies on improving this method such as changing the input values or using another kind of histogram. Although weight set is also an important key leading to the success of this method, it does not seem to get much attention. A majority of LBP-based approaches are still using the weight set of Ahonen et al.'s study, one of the first researches applying LBP to face recognition. In this study, we introduce a powerful algorithm named Heuristic Weight Search, which finds a suitable weight set for not only LBP-based approaches but also other methods using weight set to improve performance. Experiments on the FERET database prove an ability of HWS thanks to their higher accuracy than original methods.
机译:总体而言,局部二进制模式是最有效的模式识别方法之一,尤其是面部识别。已经进行了许多改进此方法的研究,例如更改输入值或使用另一种直方图。虽然权重设置也是导致此方法成功的重要关键,但似乎并没有引起太多关注。大多数基于LBP的方法仍在使用Ahonen等人研究的权重集,这是将LBP应用于面部识别的首批研究之一。在这项研究中,我们引入了一种强大的算法,即启发式权重搜索,该算法不仅为基于LBP的方法找到了合适的权重集,而且为使用权重集提高性能的其他方法找到了合适的权重集。 FERET数据库上的实验由于具有比原始方法更高的准确性而证明了HWS的功能。

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