Facial Expression Recognition from Different Angles Using DCNN for Children with ASD to Identify Emotions
Facial Expression Recognition from Different Angles Using DCNN for Children with ASD to Identify Emotions
复制标题
不同角度的面部表情识别利用DCNN为自闭症儿童识别情绪
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Damian Valles
中科院分区：
文献类型：
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作者：
Md Inzamam Ul Haque;Damian Valles
本文讨论了一个研究项目的后续工作，该项目的最终目标是建立一个移动设备应用程序，该应用程序可以利用计算机视觉和图像处理来教患有自闭症谱系障碍的儿童识别人脸表情。本文讨论了一种使用深度卷积神经网络(DCNN)的面部表情识别方法的中间工作，该方法利用不同角度的图像。卡罗林斯卡定向情感脸(KDEF)数据集已用于DCNN模型的训练和测试。该数据集包含来自五个不同角度的图像。本文的研究结果将有助于实现从任何角度识别人脸表情的最终目标。最后，对取得的成果进行了讨论，并对该项目下一步的工作进行了展望。
In this paper, continued work of a research project is discussed whose end goal is to build a mobile device application that can teach children with ASD (Autism Spectrum Disorder) to recognize human facial expressions utilizing computer vision and image processing. This paper discusses the intermediate work of a facial expression recognition approach using a deep convolutional neural network (DCNN) utilizing images from different angles. The Karolinska Directed Emotional Faces (KDEF) dataset has been used to train and test with the DCNN model. This dataset contains images from five different angles. Results of this paper will contribute to the end goal of the research which is to recognize facial expression from any angle of viewpoint. Finally, the result obtained is discussed and future work of the project is outlined.