On application of principal component analysis and linear discriminant analysis to control driver's behavior

D. S. Kulikov, V. Mokeyev
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引用次数: 0

Abstract

The article is concerned with the problem of realization to control driver's behavior for detection of some tiredness sighs at long-term hard work. The solution of the task is based on the processing images supplied by the DVR (Drive Video Registrator), principal component analysis and linear discriminant analysis. Main attention is paid to the following phases: projection images of face from original attribute area to reduction subarea of principal components, generating the special classifier according to principal components obtained with the linear discriminant analysis. The paper gives the method to increase algorithm efficiency with preliminary processing the Gabor's filter for exclusion face misses due to differences in illumination and another factor. The article estimates the algorithm accuracy and performance.
主成分分析与线性判别分析在驾驶员行为控制中的应用
本文研究了如何实现对驾驶员行为的控制,以检测驾驶员在长期辛苦工作中出现的疲劳症状。该任务的解决是基于DVR(驱动器视频注册器)提供的处理图像,主成分分析和线性判别分析。主要关注以下几个阶段:将人脸图像从原始属性区域投影到主成分约简子区域,根据线性判别分析得到的主成分生成专用分类器。本文给出了对由于光照差异和其他因素导致的排除人脸缺失的Gabor滤波器进行初步处理以提高算法效率的方法。文章对算法的精度和性能进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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