首页> 外文期刊>IEEE Transactions on Image Processing >An Example-Based Face Hallucination Method for Single-Frame, Low-Resolution Facial Images
【24h】

An Example-Based Face Hallucination Method for Single-Frame, Low-Resolution Facial Images

机译:单帧低分辨率面部图像的基于示例的幻觉方法

获取原文
获取原文并翻译 | 示例

摘要

This paper proposes a face hallucination method for the reconstruction of high-resolution facial images from single-frame, low-resolution facial images. The proposed method has been derived from example-based hallucination methods and morphable face models. First, we propose a recursive error back-projection method to compensate for residual errors, and a region-based reconstruction method to preserve characteristics of local facial regions. Then, we define an extended morphable face model, in which an extended face is composed of the interpolated high-resolution face from a given low-resolution face, and its original high-resolution equivalent. Then, the extended face is separated into an extended shape and an extended texture. We performed various hallucination experiments using the MPI, XM2VTS, and KF databases, compared the reconstruction errors, structural similarity index, and recognition rates, and showed the effects of face detection errors and shape estimation errors. The encouraging results demonstrate that the proposed methods can improve the performance of face recognition systems. Especially the proposed method can enhance the resolution of single-frame, low-resolution facial images.
机译:本文提出一种人脸幻觉方法,用于从单帧,低分辨率的面部图像中重建高分辨率的面部图像。所提出的方法是从基于实例的幻觉方法和可变形人脸模型派生而来的。首先,我们提出了一种递归误差反投影方法来补偿残留误差,以及一种基于区域的重建方法来保留局部面部区域的特征。然后,我们定义一个扩展的可变形人脸模型,其中一个扩展人脸由给定低分辨率人脸的内插高分辨率人脸及其原始高分辨率人脸组成。然后,将延伸的面部分离为延伸的形状和延伸的纹理。我们使用MPI,XM2VTS和KF数据库执行了各种幻觉实验,比较了重建误差,结构相似性指数和识别率,并显示了面部检测误差和形状估计误差的影响。令人鼓舞的结果表明,所提出的方法可以改善人脸识别系统的性能。特别地,所提出的方法可以增强单帧,低分辨率面部图像的分辨率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

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