• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文OA文献 >A scheme of human face recognition in complex environments
【2h】

A scheme of human face recognition in complex environments

机译：复杂环境下的人脸识别方案

页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Face recognition is one of the most important biometrics in computer vision and it has been broadly employed in the area such as surveillance, information security, identification, and law enforcement. Over the last few decades a considerable number of studies have been conducted in face recognition such as Principal Component Analysis (PCA), Independent Component Analysis (ICA), Linear Discriminant Analysis (LDA), and Elastic Bunch Graph Matching (EBGM), etc. What seems to be insufficient is the research in accuracy of face recognition, it could be affected by the factors such as luminance changes, pose changes, making up, complex backgrounds, head rotation, aging issues, and emotions, etc. This thesis will limit the discussions and concentrate on accuracy problem of face recognition in complex environments. The complex environments are considered as a place with a large number of people such as big office, internet cafés, airport, train and bus station, and casino etc. In these environments, the target human faces for recognizing usually mingle with moving objects. However, the face recognition in complex environments also can be described as the face recognition for several people who might be interested. Therefore, in this thesis, we target only the person (referred as the “Target User”) who is located closest to the camera and stationary. In this thesis, a new scheme is proposed to recognize human faces in such complex environments. The proposed scheme can be split into three phases. The first is Moving Object Removal (MOR). The moving object could be a pedestrian, a vehicle or other moving object. The second phase is face detection which is a technology to locate a human face in a set of images or a video. The Open Source Computer Vision (OpenCV) locates human face features such as those of eyes, ears, mouth, and nose utilizing Viola-Jones algorithm. The final stage is face recognition. If a face is detected, it will be decomposed into PCA components, and then compared to other decomposed images in a face dataset. The objective of this thesis is to propose a new scheme for human face recognition in complex environments so as to improve recognition precision and reduce false alarms. The scheme can be applied to prevent computer users against sitting too long in front of a screen.
机译：人脸识别是计算机视觉中最重要的生物识别技术之一，已广泛应用于监视，信息安全，识别和执法等领域。在过去的几十年中，已经在面部识别方面进行了大量研究，例如主成分分析（PCA），独立成分分析（ICA），线性判别分析（LDA）和弹性束图匹配（EBGM）等。面部识别的准确性研究似乎还不够，它可能受到亮度变化，姿势变化，化妆，复杂的背景，头部旋转，衰老问题和情绪等因素的影响。讨论并专注于复杂环境中人脸识别的准确性问题。复杂的环境被认为是一个拥有大量人的地方，例如大型办公室，网吧，机场，火车站和汽车站以及赌场等。在这些环境中，用于识别的目标人脸通常与移动的物体混杂在一起。但是，复杂环境中的面部识别也可以描述为可能感兴趣的几个人的面部识别。因此，在本文中，我们仅针对最靠近相机且静止不动的人（称为“目标用户”）。本文提出了一种在这种复杂环境下识别人脸的新方案。所提出的方案可以分为三个阶段。第一个是移动对象删除（MOR）。运动物体可以是行人，车辆或其他运动物体。第二阶段是面部检测，这是一种在一组图像或视频中定位人脸的技术。开源计算机视觉（OpenCV）利用Viola-Jones算法定位人脸特征，例如眼睛，耳朵，嘴巴和鼻子。最后阶段是人脸识别。如果检测到人脸，它将被分解为PCA组件，然后与人脸数据集中的其他分解图像进行比较。本文的目的是提出一种复杂环境下的人脸识别新方案，以提高识别精度，减少误报。该方案可用于防止计算机用户坐在屏幕前太长时间。

著录项

  • 作者

    Cui Wei;

  • 作者单位
  • 年度 2014
  • 总页数
  • 原文格式 PDF
  • 正文语种 en
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号