Deep unsupervised multi-modal fusion network for detecting driver distraction

	Deep unsupervised multi-modal fusion network for detecting driver distraction
	Zhang, Yuxin 1,2,3; Chen, Yiqiang 1,2,3; Gao, Chenlong 1,2,3
	2021-01-15
发表期刊	NEUROCOMPUTING
ISSN	0925-2312
卷号	421 页码:26-38
摘要	The risk of incurring a road traffic crash has increased year by year. Studies show that lack of attention during driving is one of the major causes of traffic accidents. In this work, in order to detect driver distraction, e.g., phone conversation, eating, texting, we introduce a deep unsupervised multi-modal fusion network, termed UMMFN. It is an end-to-end model composing of three main modules: multi-modal representation learning, multi-scale feature fusion and unsupervised driver distraction detection. The first module is to learn low-dimensional representation of multiple heterogeneous sensors using embedding subnetworks. The goal of multi-scale feature fusion is to learn both the temporal dependency for each modality and spatio dependencies from different modalities. The last module utilizes a ConvLSTM Encoder-Decoder model to perform an unsupervised classification task that is not affected by new types of driver behaviors. During the detection phase, a fine-grained detection decision can be made through calculating reconstruction error of UMMFN as a score for each captured testing data. We empirically compare the proposed approach with several state-of-the-art methods on our own multi-modal dataset for distracted driving behavior. Experimental results show that UMMFN has superior performance over the existing approaches. (c) 2020 Elsevier B.V. All rights reserved.
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Plan of China[2018YFC2000605] ; Beijing Natural Science Foundation[4194091] ; Beijing Municipal Science & Technology Commission[Z171100000117001]
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000593102100003
出版者	ELSEVIER
引用统计	被引频次：44[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/15970
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Chen, Yiqiang
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100190, Peoples R China 3.Beijing Key Lab Mobile Comp & Pervas Device, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Yuxin,Chen, Yiqiang,Gao, Chenlong. Deep unsupervised multi-modal fusion network for detecting driver distraction[J]. NEUROCOMPUTING,2021,421:26-38.
APA	Zhang, Yuxin,Chen, Yiqiang,&Gao, Chenlong.(2021).Deep unsupervised multi-modal fusion network for detecting driver distraction.NEUROCOMPUTING,421,26-38.
MLA	Zhang, Yuxin,et al."Deep unsupervised multi-modal fusion network for detecting driver distraction".NEUROCOMPUTING 421(2021):26-38.