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Home Security System Based on Fuzzy k-NN Classifier

机译:基于模糊K-NN分类器的家庭安全系统

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摘要

A Fuzzy k-nn Classifier for home security system we describe in this paper. Images were taken in uncontrolled indoor environment using video cameras of various qualities. Database contains 4,005 static images (in visible and infrared spectrum) of 267 subjects. Images from different quality cameras should mimic real-world conditions and enable robust face recognition algorithms testing, emphasizing different law enforcement and surveillance use case scenarios. In addition to database description, this paper also elaborates on possible uses of the database and proposes a testing protocol. A baseline Principal Component Analysis (PCA) face recognition algorithm was tested following the proposed protocol based on k-nn Classifier. Other researchers can use these test results as a control algorithm performance score when testing their own algorithms on this dataset. Database is available to research community through the procedure described at http://www.lrv.fri.uni-lj.si/facedb.html.
机译:我们在本文中描述的家庭安全系统模糊K-NN分类器。使用各种品质的摄像机在不受控制的室内环境中拍摄了图像。数据库包含267个科目的4,005静态图像(可见和红外光谱)。来自不同质量相机的图像应模拟现实世界的条件,并实现强大的人脸识别算法测试,强调不同的执法和监视用例场景。除了数据库描述外,本文还详细阐述了数据库的可能用途,并提出了一个测试协议。基于K-NN分类器的所提出的协议,测试了基线主成分分析(PCA)面部识别算法。其他研究人员可以使用这些测试结果作为在该数据集上测试自己的算法时作为控制算法性能分数。通过http://www.lrv.fri.uni-lj.si/facedb.html中描述的程序来研究社区数据库。

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