文章基本信息

标题：Multi-EmoNet: A Novel Multi-Task Neural Network for Driver Emotion Recognition
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作者：Yaodong Cui ; Yintao Ma ; Wenbo Li 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：5
页码：650-655
DOI：10.1016/j.ifacol.2021.04.155
语种：English
出版社：Elsevier
摘要：AbstractDriver’s emotion affects driving safety Hu et al. (2013), therefore monitoring driver’s emotion could benefit road safety. However, the complex illumination conditions in a vehicle cockpit significantly challenge the effectiveness of camera-based facial expression recognition (FER) systems. To solve this problem, we proposed Multi-EmoNet, a novel multi-task neural network, to classify human facial expression under illumination variations and to restore noisy images. Our experiments demonstrate these two tasks are complementary and together facilitate better network representation learning. Our approach obtains significantly better classification accuracy on images with illumination variation compared to the baseline networks. More importantly, the proposed multi-task network is a general architecture that can be applied to any noise involved image classification problem.
关键词：KeywordsEmotion RecognitionFacial Expression RecognitionIntelligent VehicleDeep learningPattern Recognition