9,000 Images of 180 People - Driver Gesture 21 Landmarks Annotation Data. This data diversity includes multiple age periods, multiple time periods, multiple gestures, multiple vehicle types, multiple time periods. For annotation, the vehicle type, gesture type, person nationality, gender, age and gesture 21 landmarks (each landmark includes the attribute of visible and invisible) were annotated. This data can be used for tasks such as driver gesture recognition, gesture landmarks detection and recognition.
For more details, please refer to the link: https://www.nexdata.ai/datasets/speechrecog/1576?source=Github
180 people, 50 images per person, including 18 static gestures, 32 dynamic gestures
gender distribution: 89 males, 91 females; age distribution: ranging from young to the elderly, the middle-aged and young people are the majorities; race distribution: Asian
In-cabin camera
multiple age periods, multiple time periods, multiple gestures
RGB camera, the resolution is 1,920*1,080
above the rearview mirror
day, evening, night
car, SUV, MPV
the image data format is .jpg, the annotation file format is .json
label the vehicle type, gesture type, person nationality, gender and age; gesture 21 landmarks (each landmark includes the attribute of visible and invisible) were annotated
the accuracy of gesture landmarks annotation is not less than 95%; the accuracies of gesture type,
Commercial License