Development of deep learning-based facial expression recognition system

Heechul Jung, Sihaeng Lee, Sunjeong Park, Byungju Kim, Junmo Kim, Injae Lee, C. Ahn
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引用次数: 51

Abstract

Deep learning is considered to be a breakthrough in the field of computer vision, since most of the world records of the recognition tasks are being broken. In this paper, we try to apply such deep learning techniques to recognizing facial expressions that represent human emotions. The procedure of our facial expression recognition system is as follows: First, face is detected from input image using Haar-like features. Second, the deep network is used for recognizing facial expression using detected faces. In this step, two different deep networks can be used such as deep neural network and convolutional neural network. Consequently, we compared experimentally two types of deep networks, and the convolutional neural network had better performance than deep neural network.
基于深度学习的面部表情识别系统的开发
深度学习被认为是计算机视觉领域的一个突破,因为大多数识别任务的世界纪录正在被打破。在本文中,我们尝试将这种深度学习技术应用于识别代表人类情感的面部表情。我们的面部表情识别系统的流程如下:首先,使用Haar-like feature从输入图像中检测人脸。其次,利用深度网络对检测到的人脸进行表情识别。在这一步中,可以使用两种不同的深度网络,如深度神经网络和卷积神经网络。因此,我们对两种类型的深度网络进行了实验比较,发现卷积神经网络比深度神经网络具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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