.png){kind=icon}
返回
Morphable model space based face super-resolution reconstruction and recognition
.png){kind=icon}
PRE
AI
DOI：10.1016/j.imavis.2012.01.005.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Super-resolution image reconstruction is the process of producing a high-resolution image from a set of low-resolution images of the same scene. For the applications of performing face evaluation and/or recognition from low-resolution video surveillance, in the past, super-resolution image reconstruction was mainly used as a separate preprocessing step to obtain a high-resolution image in the pixel domain that is later passed to a face feature extraction and recognition algorithm. Such three-stage approach suffers a high degree of computational complexity. A low-dimensional morphable model space based face super-resolution reconstruction and recognition algorithm is proposed in this paper. The approach tries to construct the high-resolution information both required by reconstruction and recognition directly in the low dimensional feature space. We show that comparing with generic pixel domain algorithms, the proposed approach is more robust and more computationally efficient. (C) 2012 Elsevier B.V. All rights reserved.
Keyword:
Super-resolution
Feature space
Image sequence
Image reconstruction
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.2
论文数:
4.1K
被引数:
6.7K
机构
引用论文
.png){kind=icon}
分享收藏
查看更多内容