Machine Vision to Alert Roadside Personnel of Night Traffic Threats

In the United States, every year, several people whose job takes them to the sides of roads, are injured or killed by roadside collisions. This could be avoided if a warning signal could be sent to them. In this paper, we describe a machine-vision based alerting system which detects and tracks headl...

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Bibliographic Details
Published inIEEE transactions on intelligent transportation systems Vol. 19; no. 10; pp. 3245 - 3254
Main Authors Wang, Liang, Horn, Berthold K. P.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.10.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
alerting system
Automobiles
Cameras
convex hull updating
danger identification
Fixtures
Headlamps
Image detection
Injury prevention
Labeling
Law enforcement
Machine vision
multi object tracking
Night
Personnel
Smart phones
Smartphones
Vision systems
“Blob” detection
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Summary:In the United States, every year, several people whose job takes them to the sides of roads, are injured or killed by roadside collisions. This could be avoided if a warning signal could be sent to them. In this paper, we describe a machine-vision based alerting system which detects and tracks headlamps of cars in night traffic. The system automatically computes a "normal traffic" region in the image. Unusual trajectories of cars are detected when the images of their headlamps move out of that region. The system promptly sends a warning signal once a risk has been identified. The system runs on the Android smart phones, which are mounted on cars or on roadside fixtures.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2017.2772225