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首页> 外文会议>International Symposium on Computer and Information Sciences(ISCIS 2004); 20041027-29; Kemer-Antalya(TR) >Boosting Face Recognition Speed with a Novel Divide-and-Conquer Approach
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Boosting Face Recognition Speed with a Novel Divide-and-Conquer Approach

机译：一种新颖的分而治之方法提高人脸识别速度

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摘要

Computational and storage space efficiencies of a novel approach based on appearance-based statistical methods for face recognition are studied. The new approach is a low-complexity divide-and-conquer method implemented as a multiple-classifier system. Appearance-based statistical algorithms are used for dimensionality reduction followed by distance-based classifiers. An appropriate classifier combination method is used to determine the resulting face recognized. FERET database and FERET Evaluation Methodology are used in all experimental evaluations. Time and space complexities of the proposed approach indicate that it outperforms the holistic Principal Component Analysis, Linear Discriminant Analysis and Independent Component Analysis in computational and storage space efficiencies. The experimental results show that the proposed approach also provides better recognition performance on frontal images.
机译：研究了一种基于基于外观的统计方法进行人脸识别的新方法的计算和存储空间效率。新方法是实现为多分类器系统的低复杂度分治方法。基于外观的统计算法用于降维，然后是基于距离的分类器。适当的分类器组合方法用于确定识别出的结果面部。所有实验评估均使用FERET数据库和FERET评估方法。该方法在时间和空间上的复杂性表明，在计算和存储空间效率方面，其性能优于整体主成分分析，线性判别分析和独立成分分析。实验结果表明，该方法在正面图像上也具有较好的识别性能。

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