A Short Review of Methods for Face Detection and Multifractal Analysis

Moi Hoon Yap, H. Ugail, R. Zwiggelaar, Bashar A. Rajoub, Victoria Doherty, S. Appleyard, Gemma Hurdy
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引用次数: 21

Abstract

The purpose of this paper is to present short reviews the face detection techniques and to study the effect of Multifractal analysis in detecting facial features. In reviewing the existing techniques, we have compared the performance of Nilsson et al’s algorithm, Haar Training implemented within Open Source Computer Vision Library (OpenCV) and Keinzle’s algorithm in face detection. Then, we have produced some experimental results suggesting that the Multifractal approach would help to extract key facial features of a human face. We conclude the paper with some discussions on how the work can be taken further.
人脸检测与多重分形分析方法综述
本文的目的是简要介绍人脸检测技术,并研究多重分形分析在人脸特征检测中的作用。在回顾现有技术时,我们比较了Nilsson等人的算法、开源计算机视觉库(OpenCV)中实现的Haar训练和Keinzle的人脸检测算法的性能。然后,我们产生了一些实验结果,表明多重分形方法将有助于提取人脸的关键面部特征。最后,我们对如何进一步开展这项工作进行了一些讨论。
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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