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103,282-Images Driver Behavior Annotation Data

dangerous behaviors
fatigue behaviors
visual movement behaviors
72 facial landmarks
face attributes
gesture bounding boxes
seatbelt bounding boxes
pupil landmarks
behavior categories
multiple ages
multiple time periods
In-car Cameras
RGB and infrared channels.emini
pair
couple
matches
two
brace
pairs
deuce
double
doubles
duality
twin
match
combine
twosome
duo
dyad
mates
duet
duplicate
gemini
the
twins
similitude
yoke
binaries
counterparts
mate
analogs
counterpart
couples
doublets
look-alike
parallel
span
deuces
mirror
images
brothers
clone
duplexes
nuts
rocks
alter
egos
balls
clones
combo
doublet
dyads
equivalents
join
pair-offs
plumsrn

103,282-Images Driver Behavior Annotation Data. The data includes multiple ages, multiple time periods and behaviors (Dangerous behaviors, Fatigue behaviors, Visual movement behaviors). In terms of annotation, 72 facial landmarks (including pupils), face attributes, gesture bounding boxes, seatbelt bounding boxes, pupil landmarks and behavior categories were annotated in the data. This data can be used for tasks such as driver behavior analysis.

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This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
SpecificationsSpecifications
Data size
103,282 images
Population
gender distribution: male, female, race distribution: Asian, age distribution: 18~30 years old, 31~45 years old, 46~60 years old
Collection environment
In-car Cameras
Collection diversity
multiple ages, multiple time periods and behaviors(Dangerous behaviors, Fatigue behaviors, Visual movement behaviors)
Collection device
binocular camera of RGB and infrared channels, the resolutions are 640x480
Collection time
daytime, evening and night
Image parameter
the image format is .jpeg, the annotated file format is .json
Annotation
72 facial landmarks (including pupils), face attributes, gesture bounding boxes, seatbelt bounding boxes, pupil landmarks, behavior categories
Desensitization
no sensitive information
Accuracy
the accuracy of facial landmarks annotation is not less than 95%; the accuracies of gesture bounding box, seatbelt bounding box, face attribute and driver behavior label are not less than 95%
Sample Sample
  • Waiting For Data
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Driver behavior acquisition data driver behavior acquisition driver data acquisition driver behavior data
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dangerous behaviors fatigue behaviors visual movement behaviors multiple ages multiple time periods multiple races n-car Cameras RGB and infrared channels feeling passion sentiment excitement sensation affection intensity ardor sensibility fervor vehemence love response warmth zeal emotional pathos agitation spirit affectivity enthusiasm fervency perturbation impression sympathy sadness sentimentality thrill eagerness poignancy commotion emotionalism fire soul animation emotionality responsiveness sensitiveness disturbance energy expression tenderness pitifulness plaintiveness poignance sentiments vibes anger empathy feelings
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dangerous behaviors fatigue behaviors visual movement behaviors multiple ages multiple time periods In-car Cameras RGB and infrared channels
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