1,350 Drivers – Driver Behavior Recognition Dataset (RGB & IR)

driver behavior recognition dataset

in-cabin driver monitoring

driver fatigue detection

dangerous driving dataset

RGB IR driver dataset

automotive AI driver behavior

driver visual movement dataset

multimodal driver dataset

This dataset includes diverse drivers across multiple ages, time periods, and lighting conditions, with annotated behaviors including dangerous driving, fatigue, and visual movement behaviors. In terms of device, binocular cameras of RGB and infrared channels were applied. This data can be used for tasks such as driver behavior analysis, fatigue and drowsiness detection, dangerous driving recognition and driver attention and visual movement monitoring.

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Specifications

Data size

1,350 people

Population distribution

gender distribution: 679 males, 671 females; race distribution: Vietnam, Indonesia, etc.; age distribution: 18~45 years old, 46~60 years old, over 60 years old

Collecting environment

in-car Cameras

Data diversity

multiple age periods, multiple time periods, multiple lighting and behaviors (Dangerous behavior, Fatigue behavior, Visual movement behavior)

Device

visible light and infrared binocular camera, resolution 1,920x1,080

Shooting position

the center of the inside rearview mirror of the car, above the center console in the car, above the left A-pillar in the car, steering wheel position, rearview mirror wide angle lens position

Collecting time

day, evening, night

Collecting light

normal light, weak light, strong light

Vehicle Type

car, SUV, MVP, truck, bus

Data Format

the video data format is .mp4

Accuracy

according to the accuracy of each person's acquisition action, the accuracy exceeds 95%;the accuracy of label annotation is not less than 95%

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