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28,972 Images - Driver Face Detection & Face 96 Landmarks Annotation Data

DMS，Drivers

Face Detection

Facial 96 Landmarks

100 People - Face Detection & Face 96 Landmarks Annotation Data. The data includes multiple ages, multiple time periods and multiple races (Caucasian, Black, Indian). The driver behaviors includes dangerous behavior, fatigue behavior and visual movement behavior. In terms of device, infrared cameras were applied. In terms of annotation, each individual consists of 274 to 299 photos, with annotations for detected facial bounding boxes and 96 facial landmarks. The data can be used for tasks such as facial detection, 96 facial landmark 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

100 people, 28,972 images, each person contains 274-298 images

Population distribution

Gender distribution: 50 males, 50 females; race distribution: 50 Caucasians, 30 Blacks, and 20 Browns; age distribution: 51 people aged from 18 to 30, 45 people aged from 31 to 45, 4 people aged from 46 to 60

Collecting environment

In-car Cameras

Data diversity

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

Device

Infrared cameraes, the resolutions is 640x480

Shooting position

the center of the inside rear view mirror of the car, above the center console in the car, above the left A-pillar in the car

Collecting time

day, evening and night

Vehicle Type

car, SUV

Data format

image data format is .jpg, annotation document format is .json

Annotation content

annotations include detected facial bounding boxes and 96 facial landmarks

Accuracy rate

face Detection Bounding Box Accuracy: the detection box is considered qualified if the offset does not exceed 5 pixels on all four sides, with a qualification rate of no less than 95%; Facial Landmark Accuracy: the accuracy rate of facial landmark annotation must be no less than 95%.

Sample

Sample

Recommended Datasets

Recommended Dataset

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Driver Gesture Collection Data Driver Gesture Collection Driver Collection Data Driver Gesture Data

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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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Driver behavior acquisition data driver behavior acquisition driver data acquisition driver behavior data wide-angle camera

122 People - Passenger Behavior Recognition Data

122 People - Passenger Behavior Recognition Data. The data includes multiple age groups, multiple time periods and multiple races (Caucasian, Black, Indian). The passenger behaviors include passenger normal behavior, passenger abnormal behavior(passenger carsick behavior, passenger sleepy behavior, passenger lost items behavior). In terms of device, binocular cameras of RGB and infrared channels were applied. This data can be used for tasks such as passenger behavior analysis.

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

304 People Multi-race - Driver Behavior Collection Data

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dangerous behaviors fatigue behaviors visual movement behaviors multiple ages multiple time periods multiple races RGB and infrared channels In-car Cameras

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