• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>ACM Computing Surveys >Synthesis of Facial Expressions in Photographs: Characteristics, Approaches, and Challenges
【24h】

Synthesis of Facial Expressions in Photographs: Characteristics, Approaches, and Challenges

机译：照片中面部表情的合成：特征，方法和挑战

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The synthesis of facial expressions has applications in areas such as interactive games, biometrics systems, and training of people with disorders, among others. Although this is an area relatively well explored in the literature, there are no recent studies proposing to systematize an overview of research in the area. This systematic review analyzes the approaches to the synthesis of facial expressions in photographs, as well as important aspects of the synthesis process, such as preprocessing techniques, databases, and evaluation metrics. Forty-eight studies from three different scientific databases were analyzed. From these studies, we established an overview of the process, including all the stages used to synthesize expressions in facial images. We also analyze important aspects involved in these stages such as methods and techniques of each stage, databases, and evaluation metrics. We observed that machine learning approaches are the most widely used to synthesize expressions. Landmark identification, deformation, mapping, fusion, and training are common tasks considered in the approaches. We also found that few studies used metrics to evaluate the results, and most studies used public databases. Although the studies analyzed generated consistent and realistic results while preserving the identity of the subject, there are still research themes to be exploited.
机译：面部表情的合成已在诸如互动游戏，生物识别系统以及对残障人士进行培训等领域中得到应用。尽管这是文献中相对较好地探索的领域，但是最近没有提议将该领域的研究概述系统化的研究。该系统综述分析了照片中面部表情的合成方法，以及合成过程的重要方面，例如预处理技术，数据库和评估指标。分析了来自三个不同科学数据库的48个研究。通过这些研究，我们对过程进行了概述，包括用于合成面部图像中的表情的所有阶段。我们还将分析这些阶段涉及的重要方面，例如每个阶段的方法和技术，数据库以及评估指标。我们观察到机器学习方法是最广泛用于合成表达式的方法。地标识别，变形，制图，融合和训练是方法中考虑的常见任务。我们还发现，很少有研究使用指标来评估结果，而大多数研究则使用公共数据库。尽管所分析的研究在保持受试者身份的同时产生了一致且现实的结果，但仍有一些研究主题可以利用。

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