Driver Behavior Recognition using Recurrent Neural Network in Multiple Depth Cameras Environment

Ying Wei Chuang, Chien Hao Kuo, Shih Wei Sun, Pao Chi Chang

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

To improve the driving safety triggered by driver's behavior recognition in an in-car environment, we propose to use depth cameras mounted in a car to generate behavior models generated by a deep learning algorithm for a driver's behavior classification. The contribution of this paper is trifold: 1) The proposed multi-view driver behavior recognition system can handle the occlusion problem happened in one of the cameras; 2) Using the recurrent neural network can effectively recognize the continuous time behavior; 3) the average recognition accuracy of proposed systems can achieve 83% and 88%, respectively.

Original languageEnglish
Article numberAVM-056
JournalIS and T International Symposium on Electronic Imaging Science and Technology
Volume2019
Issue number15
DOIs
StatePublished - 13 Jan 2019
Event2019 Autonomous Vehicles and Machines Conference, AVM 2019 - Burlingame, United States
Duration: 13 Jan 201917 Jan 2019

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