Real Time System for Facial Analysis
Real Time System for Facial Analysis
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实时面部分析系统
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
H. Huttunen
中科院分区：
文献类型：
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作者：
Janne Tommola;Pedram Ghazi;Bishwo Adhikari;H. Huttunen
本文描述了一个实时人脸分析系统的结构。该系统可以识别出现在摄像头前的用户的年龄、性别和面部表情。所有组件都基于卷积神经网络，我们在常用的训练和评估集上研究卷积神经网络的准确性。这项工作的一个关键贡献是描述了帧抓取、人脸检测和三种类型识别的处理线程之间的相互作用。用于执行系统的python代码使用通用库——keras/tensorflow、opencv和dlib——可以下载。
In this paper we describe the anatomy of a real-time facial analysis system. The system recognizes the age, gender and facial expression from users in appearing in front of the camera. All components are based on convolutional neural networks, whose accuracy we study on commonly used training and evaluation sets. A key contribution of the work is the description of the interplay between processing threads for frame grabbing, face detection and the three types of recognition. The python code for executing the system uses common libraries--keras/tensorflow, opencv and dlib--and is available for download.