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1,335 People - Driver Gesture Recognition Data

Driver Gesture Collection Data

Driver Gesture Collection

Driver Collection Data

Driver Gesture Data

1,335 People - Driver Gesture Recognition Data covers multiple age groups, multiple time periods, and multiple gestures. In terms of acquisition equipment, visible light and infrared binocular cameras are used. Each person collected 18 static gestures and 23 dynamic gestures. Static gestures included fist-clenching gestures and heart-to-heart gestures, and dynamic gestures included index finger clicks and two-finger clicks. This set of driver gesture recognition data can be used for tasks such as driver gesture recognition.

This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.

Specifications

Specifications

Data size

1,335 people, each person collects 18 static gestures and 23 dynamic gestures

Gender distribution

666 males, 669 females

Nationality distribution

Vietnam, Indonesia, etc.

Age distribution

18~45 years old, 46~60 years old, over 60 years old

Collecting environment

in-car camera shooting scene

Data diversity

covering multiple gestures, multiple age groups, and multiple time periods

Device

visible light and infrared binocular camera, resolution are 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, the image data format is .jpg

Accuracy

based on the accuracy of the actions, the accuracy exceeds 95%;the label naming accuracy rate is over 95%

Sample

Sample

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Recommended Dataset

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1,000 People - Passenger Behavior Recognition Data

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Passenger normal behavior passenger carsick behavior passenger sleepy behavior passenger lost items behavior multiple age groups multiple time periods

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