基于深度学习的人脸分析研究进展

发布时间：2018-07-05 05:13

  本文选题：深度学习 + 卷积神经网络　； 参考：《厦门大学学报(自然科学版)》2017年01期

【摘要】：近年来,基于深度学习的人脸分析取得了巨大的进步,成为计算机视觉领域最为活跃的研究方向之一.为了进一步推动深度学习和人脸分析的研究,结合近年已发表的相关文献,对基于深度学习的人脸分析技术进行综述.首先,简要概述深度学习及其发展历史,并分析深度学习有效性原因.然后,按照任务目的的不同,将人脸分析分成了人脸检测、人脸关键点检测、人脸识别、人脸属性识别等任务进行详细的介绍和讨论,重点分析各种任务现阶段存在的主要问题.接着,介绍人脸分析中常用的人脸数据库.最后,讨论深度学习和人脸分析面临的主要挑战,并给出结论.
[Abstract]:In recent years, face analysis based on deep learning has made great progress and become one of the most active research directions in the field of computer vision. In order to further promote the research of depth learning and face analysis, combined with the related literature published in recent years, this paper summarizes the technology of face analysis based on depth learning. First of all, it briefly summarizes the history of deep learning and its development, and analyzes the reasons for the effectiveness of depth learning. Then, according to the different purpose of the task, face analysis is divided into face detection, face key point detection, face recognition, face attribute recognition and other tasks for detailed introduction and discussion. Focus on the analysis of various tasks at the present stage of the main problems. Then, the face database commonly used in face analysis is introduced. Finally, the main challenges of depth learning and face analysis are discussed and the conclusions are given.
【作者单位】： 厦门大学信息科学与技术学院福建省智慧城市感知与计算重点实验室;
【基金】：国家自然科学基金(61571379,61472334)
【分类号】：TP391.41
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本文编号：2099061