research-article

Dangerous Driving Behavior Detection with Attention Mechanism

Authors:

Kun Wang,

Xianqiao Chen,

Rui GaoAuthors Info & Claims

ICVIP '19: Proceedings of the 3rd International Conference on Video and Image Processing

Pages 57 - 62

https://doi.org/10.1145/3376067.3376101

Published: 25 February 2020 Publication History

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Abstract

In order to reduce the incidence of traffic accidents caused by dangerous driving, a dangerous driving behavior recognition model based on convolutional neural network (CNN) and long short-term memory network (LSTM) is proposed. Aiming at the problem of low accuracy of the network model identification, the algorithm is optimized by introducing the unsupervised attention mechanism. The model focuses on a specific visual area and improves the recognition accuracy of the algorithm to some extent by integrating the attention weighted module and the convolution LSTM. The experimental results show that the detection accuracy and detection rate of the algorithm are improved compared with the Two-Stream method and C3D behavior recognition algorithm in the dangerous driving behavior recognition task.

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Cited By

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Nguyen HNguyen TTran THoang VLe TTran TVu H(2022)End-to-end deep learning-based framework for driver action recognition2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR)10.1109/MAPR56351.2022.9924944(1-6)Online publication date: Oct-2022
https://doi.org/10.1109/MAPR56351.2022.9924944
Liu JLiu YTian CZhao MZeng XSong L(2022)Multi-level Attention Fusion for Multimodal Driving Maneuver Recognition2022 IEEE International Symposium on Circuits and Systems (ISCAS)10.1109/ISCAS48785.2022.9937710(2609-2613)Online publication date: 28-May-2022
https://doi.org/10.1109/ISCAS48785.2022.9937710
Jegham IKhalifa AAlouani IMahjoub M(2021)Soft Spatial Attention-Based Multimodal Driver Action Recognition Using Deep LearningIEEE Sensors Journal10.1109/JSEN.2020.301925821:2(1918-1925)Online publication date: 15-Jan-2021
https://doi.org/10.1109/JSEN.2020.3019258

Index Terms

Dangerous Driving Behavior Detection with Attention Mechanism
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
        Activity recognition and understanding

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ICVIP '19: Proceedings of the 3rd International Conference on Video and Image Processing

December 2019

270 pages

ISBN:9781450376822

DOI:10.1145/3376067

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Shanghai Jiao Tong University: Shanghai Jiao Tong University
Xidian University
TU: Tianjin University

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Association for Computing Machinery

New York, NY, United States

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Published: 25 February 2020

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ICVIP 2019: 2019 the 3rd International Conference on Video and Image Processing

December 20 - 23, 2019

Shanghai, China

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Nguyen HNguyen TTran THoang VLe TTran TVu H(2022)End-to-end deep learning-based framework for driver action recognition2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR)10.1109/MAPR56351.2022.9924944(1-6)Online publication date: Oct-2022
https://doi.org/10.1109/MAPR56351.2022.9924944
Liu JLiu YTian CZhao MZeng XSong L(2022)Multi-level Attention Fusion for Multimodal Driving Maneuver Recognition2022 IEEE International Symposium on Circuits and Systems (ISCAS)10.1109/ISCAS48785.2022.9937710(2609-2613)Online publication date: 28-May-2022
https://doi.org/10.1109/ISCAS48785.2022.9937710
Jegham IKhalifa AAlouani IMahjoub M(2021)Soft Spatial Attention-Based Multimodal Driver Action Recognition Using Deep LearningIEEE Sensors Journal10.1109/JSEN.2020.301925821:2(1918-1925)Online publication date: 15-Jan-2021
https://doi.org/10.1109/JSEN.2020.3019258

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Robust GAN Based on Attention Mechanism

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