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Reduced complexity face recognition using advanced correlation filters and Fourier subspace methods for biometric applications.

机译：使用先进的相关滤波器和傅里叶子空间方法，可降低生物识别应用中的复杂性。

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摘要

This thesis presents recent research in the design of various Fourier based methods; ranging from Advanced Correlation Filters to Frequency Subspace Methods for face recognition in Biometric Applications. In particular we investigate how to perform reliable face verification for biometrics with particular focus on achieving illumination tolerance. Most Biometric applications can assume a partially co-operative user, therefore pose variations seen during test phase are assumed to be representative samples seen during the training phase. Illumination conditions of the subject can not be controlled as verification can occur anywhere where the user might not have control of their surrounding illumination conditions. Development of reduced complexity algorithms for performing face verification on limited resource computing platforms such as System-on-Chip implementations or PDA platforms are presented. This work shows that we can simplify our algorithms to produce biometric filters that only require 2 bits/per/frequency of storage, leading to templates requiring only 127 bytes of storage.; Spatial subspace methods are among the most common face recognition algorithms; however their draw back includes sensitivity to shifts of the test image, have difficulty or fail in the presence of extreme illumination and can not handle occlusions. While certain subspace algorithms are designed to handle one of these issues, they face difficulties trying to build tolerance to all of these distortions. This thesis present novel advancements in linking advanced correlation filters and subspace methods to provide hybrid PCA-correlation filters which are referred to as 'Corefaces'. These type of filters union the advantages of both worlds; efficient subspace representation of range of distortions and the shift-invariance, illumination tolerance and ability to handle partial test images featured by proposed advanced correlation filter approaches. Furthermore this research further examines how Principal Component Linear Subspaces are synthesized and presents reformulations that use Fourier transforms to achieve fast classification in a shift-invariant manner.; This thesis also details other proposed advanced correlation filters designs for increased efficiency towards building a real-time face verification system and addresses reduced complexity implementations of various parts of the system. We also address the issue of cancellability of biometric templates, proposing a novel encryption method where verification is performed directly in the encrypted domain while still preserving attractive properties such as linearity and shift invariance. Several new correlation filters are also proposed during the course of this research which offer merit improvement in speed, design or performance over current designs. While the focus of this thesis research is on face biometrics, the research and methods covered can be applied to any other biometrics such as fingerprint and iris.
机译：本文介绍了各种基于傅立叶方法设计的最新研究。从高级相关滤波器到频率子空间方法，可用于生物识别应用中的人脸识别。特别是，我们研究了如何针对生物识别技术执行可靠的人脸验证，尤其侧重于实现光照耐受性。大多数生物特征识别应用程序都可以假设是部分合作的用户，因此，假设在测试阶段看到的姿势变化是在训练阶段看到的代表性样本。不能控制对象的照明条件，因为验证可能发生在用户可能无法控制其周围照明条件的任何地方。提出了用于在有限资源计算平台（例如片上系统实现或PDA平台）上执行面部验证的降低复杂度的算法的开发。这项工作表明，我们可以简化算法，以生成仅需要2位/每个/频率存储的生物特征过滤器，从而使模板仅需要127个字节的存储。空间子空间方法是最常见的人脸识别算法。然而，它们的缺点包括对测试图像偏移的敏感性，在极端照明条件下有困难或失败，并且不能处理遮挡。虽然某些子空间算法旨在处理这些问题之一，但它们在尝试建立对所有这些失真的容忍度时面临困难。本文提出了在链接高级相关滤波器和子空间方法以提供称为“ Corefaces”的混合PCA相关滤波器方面的新颖进展。这些类型的过滤器结合了两个方面的优势。有效的子空间表示畸变的范围以及平移不变性，照明容忍度和处理部分测试图像的能力，这些功能由建议的高级相关滤波器方法实现。此外，本研究进一步研究了如何合成主分量线性子空间，并提出了使用傅立叶变换以不变移位的方式实现快速分类的重构。本文还详细介绍了其他提议的高级相关滤波器设计，以提高构建实时面部验证系统的效率，并解决了系统各个部分的复杂性降低的实现。我们还解决了生物识别模板可取消性的问题，提出了一种新颖的加密方法，该方法可以直接在加密域中进行验证，同时仍保留线性和移位不变性等吸引人的特性。在本研究过程中，还提出了几种新的相关滤波器，这些滤波器相对于当前的设计在速度，设计或性能方面都有显着提高。尽管本文研究的重点是面部生物特征，但是所涵盖的研究和方法可以应用于任何其他生物特征，例如指纹和虹膜。

著录项

  • 作者

    Savvides, Marios.;

  • 作者单位

    Carnegie Mellon University.;

  • 授予单位 Carnegie Mellon University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2004
  • 页码 271 p.
  • 总页数 271
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

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