2019
DOI: 10.1109/access.2019.2917213
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Video-Based Abnormal Driving Behavior Detection via Deep Learning Fusions

Abstract: Video-based abnormal driving behavior detection is becoming more and more popular for the time being, as it is highly important in ensuring safeties of drivers and passengers in the vehicle, and it is an essential step in realizing automatic driving at the current stage. Thanks to recent developments in deep learning techniques, this challenging detection task can be largely facilitated via the prominent generalization capability of sophisticated deep learning models as well as large volumes of video clips whi… Show more

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Cited by 27 publications
(9 citation statements)
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References 42 publications
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“…The archived model had 81.66% accuracy. Distracted behavior is classified in papers [102], [103] as texting with the right and left hands, talking on the phone using the right and left hands, drinking, reaching, applying makeup, and talking to passengers using CNN based algorithms. The algorithm achieved 99% accuracy.…”
Section: E Drivers' Statusmentioning
confidence: 99%
See 1 more Smart Citation
“…The archived model had 81.66% accuracy. Distracted behavior is classified in papers [102], [103] as texting with the right and left hands, talking on the phone using the right and left hands, drinking, reaching, applying makeup, and talking to passengers using CNN based algorithms. The algorithm achieved 99% accuracy.…”
Section: E Drivers' Statusmentioning
confidence: 99%
“…Accident Analysis and Prevention [58], [66], [83], [87], [89], [93], [94], [105], [116] Transportation Research Part F: Traffic Psychology and Behavior [40], [46], [104], [109], [111], [113], [115], [122] IEEE Access [61], [91], [97], [100], [101], [103] Journal of Safety Research [112], [114], [118], [119] Type of behavior Papers Abnormal driver behavior [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51],…”
Section: Source Publication Venue References Journal Articlementioning
confidence: 99%
“…W. Huang et al [102] have proposed three video-based behavior detection techniques for abnormal driving using three deep learning-based fusion model. The proposed models WGD (wide group densely network), WGRD (wide group residual densely network) and AWGRD (alternative wide group residual densely network) are motivated by DenseNet which is based on the densely connected convolutional network.…”
Section: A Comparative Study Of Driver Distraction Detection Techniqmentioning
confidence: 99%
“…The third category includes distracted driving behaviors influenced by the environment, such as caring for children or paying long-term attention to dramatic situations outside the automobile. Among the above abnormal driving behaviors, mobile phones have emerged as an essential component in modern abnormal driving [ 5 ].…”
Section: Introductionmentioning
confidence: 99%