DocumentCode
234786
Title
Detecting Driver Use of Mobile Phone Based on In-Car Camera
Author
Dan Wang ; Mingtao Pei ; Lan Zhu
Author_Institution
Beijing Lab. of Intell. Inf. Technol., Beijing Inst. of Technol., Beijing, China
fYear
2014
fDate
15-16 Nov. 2014
Firstpage
148
Lastpage
151
Abstract
It is dangerous for drivers to make a call while driving, as it could easily divert the drivers´ attention. In this paper, we present a novel method to detect the driver use of mobile phone based on an in-car camera. The in-car camera is mounted on the front windshield to capture the video of the driver during driving, and an activity parsing algorithm is employed to identify whether the driver is using a mobile phone. We decompose the phoning activity into three actions and use the And-Or Graph (AoG) to represent the hierarchically compositions of the phoning activity and the temporal relationship between the actions. An online parsing algorithm for AoG based on Early´s parser is implemented to parse the video and detect the driver use of mobile phone. Experiment results on collected video data set shows that the proposed method can detect the driver use of mobile phone precisely. This method could be used as a supplement of the safety device inside the vehicle.
Keywords
automobiles; automotive components; cameras; driver information systems; gesture recognition; image capture; road safety; smart phones; video signal processing; AoG; activity parsing algorithm; and-or-graph; driver attention; driver mobile phone use detection; front windshield; hierarchic composition representation; in-car camera; online parsing algorithm; phoning activity; safety device; temporal relationship; video capture; video data set collection; video parsing; Cameras; Ear; Face; Image color analysis; Mobile handsets; Skin; Vehicles; driver assistant system; driver use of mobile phone; in-car camera;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Security (CIS), 2014 Tenth International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4799-7433-7
Type
conf
DOI
10.1109/CIS.2014.12
Filename
7016871
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