602 People –3,010 Images Multi-Races Human Body Semantic Segmentation Data

Human body segmentation

different poses

different ages

different races

different collection backgrounds

different scenes.

602 People –3,010 Images Multi-Races Human Body Semantic Segmentation Data,The data diversity includes headphones, body, background,and glasses.In terms of annotation, we adpoted segmentation annotations on headphones, body, background and glasses.The data can be used for tasks such as human body segmentation and the behavior detection of Video conference.

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Specifications

Data size

602 people, 5 images for each person

Collection environment

Office, coffee shop, supermarket, apartment

Race distribution

151 Asian people, 151 black people, 150 Caucasians people, 150 brown people ,ranging from teenager to middle-aged people, (Aged between 16 and 60)

Gender distribution

301 males, 301 females

Data diversity

different poses, different ages, different races, different collection backgrounds

Device

computer, cellphone

Collecting angles

eye-level angle

Data format

the image data format is .jpg, the annotation file (mask) format is .png

Annotation content

segmentation annotation of headphones, body, background, glasses

Accuracy

based on the accuracy of the actions, the accuracy is more than 97%; Accuracy of semantic segmentation annotation: for each object, the mask edge location errors in x and y directions are less than 5 pixels, and the category label was correctly labeled, which were considered as a qualified annotation; Annotation accuracy: each object is regarded as the unit, annotation accuracy is more than 97%

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