A Facial Expression Recognition Approach Using DCNN for Autistic Children to Identify Emotions

Md Inzamam Ul Haque, Damian Valles
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引用次数: 33

Abstract

In this paper, an initial work of a research is discussed which is to teach young autistic children recognizing human facial expression with the help of computer vision and image processing. This paper mostly discusses the initial work of facial expression recognition using a deep convolutional neural network. The Kaggle's FER2013 dataset has been used to train and experiment with a deep convolutional neural network model. Once a satisfactory result is achieved, the dataset is modified with pictures of four different lighting conditions and each of these datasets is again trained with the same model. This is necessary for the end goal of the research which is to recognize facial expression in any possible environment. Finally, the comparison between results with different datasets is discussed and future work of the project is outlined.
基于DCNN的自闭症儿童面部表情识别方法
本文讨论了利用计算机视觉和图像处理技术来教自闭症儿童识别人类面部表情的初步研究工作。本文主要讨论了基于深度卷积神经网络的面部表情识别的初步工作。Kaggle的FER2013数据集已用于深度卷积神经网络模型的训练和实验。一旦获得满意的结果,数据集将被修改为四种不同照明条件的图片,并且每个数据集再次使用相同的模型进行训练。这对于研究的最终目标是在任何可能的环境中识别面部表情是必要的。最后,对不同数据集的结果进行了比较,并对项目的未来工作进行了概述。
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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