01515210

Component

https://doi.org/10.3141/2468-01

Several studies have shown that cyclists can reduce the risk of severe head injuries by wearing a helmet. A system is proposed to collect cyclist helmet usage data automatically from video footage. Computer vision techniques are used to track the moving objects and then to analyze the object trajectories and speed profiles to identify cyclists. Image features are extracted from a region around the cyclist’s head. Support vector machines determine whether the cyclist is wearing a helmet. The system can be approximately 90% accurate in cyclist classification when provided with accurate tracks of the cyclist’s head. Even for situations in which obtaining video to track a cyclist is challenging, the proposed method provides an effective retrieval system, potentially reducing the number of video records that must be analyzed manually to find instances of cyclists not wearing helmets.

01557587

14-1147

English

pp 1–10

2014

Transportation Research Record: Journal of the Transportation Research Board

9780309295659

Print

Figures (7) ; References (53) ; Tables (2)

Bicycle helmets; Computer vision; Cyclists; Data collection; Pattern recognition systems; Traffic safety; Video

Support vector machines

Data and Information Technology; Pedestrians and Bicyclists; Safety and Human Factors; Vehicles and Equipment; I91: Vehicle Design and Safety

TRIS, TRB, ATRI

Jan 27 2014 2:27PM

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