en

Please fill in your name

Mobile phone format error

Please enter the telephone

Please enter your company name

Please enter your company email

Please enter the data requirement

Successful submission! Thank you for your support.

Format error, Please fill in again

Confirm

The data requirement cannot be less than 5 words and cannot be pure numbers

15 People - 22 Landmarks Annotation Data of 3D Human Body

Human body instance segmentation
Human body landmarks
3D
Multiple poses
Multiple scenes

15 People - 22 Landmarks Annotation Data of 3D Human Body. The dataset diversity includes multiple scenes, different ages, different costumes, different human body sitting postures. In terms of annotation, we annotate the 2D and 3D coordinates of the 22 landmarks of the human body, landmark attributes, the rectangular frame of the human body. The dataset can be used for tasks such as human body instance segmentation and human behavior recognition.

Paid Datasets
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
SpecificationsSpecifications
Data size
15 people, 21,210 images
Population distribution
gender distribution: 6 males, 9 females; age distribution: 11-27 years old
Collecting environment
home environment, office environment
Data diversity
multiple scenes, different ages, different costumes, different human body sitting postures
Device
2D camera: logitech Brio 4K Pro, the resolution is 4K; 3D camera: realsense L515, the resolution is 1,920*1,080
Data format
the image data format is .jpg, the annotation file format is .json, the camera parameter file format is .json, the point cloud file format is .pcd
Collecting content
collecting the 2D and 3D images of various sitting positions of the human body (3D depth image and 4k 2D RGB image have been registered)
Annotation content
annotating the 2D and 3D coordinates of the 22 landmarks of the human body, landmark attributes, the rectangular frame of the human body
Accuracy
The mask edge location errors in x and y directions are less than 3 pixels, which is considered as a qualified annotation; Based on the landmarks, the accuracy rate shall be more than 95%, annotating accuracy = number of correct annotations / total number of annotations; The accuracy rate of label shall be more than 97%.
Sample Sample
  • Waiting For Data
Recommended DatasetsRecommended Dataset
Tell Us Your Special Needs

By submitting, I agree to the Privacy Protection

7b3a5d01-bb3a-48a2-a96f-5d877574032c

3d98952e-e17d-4d7d-81b8-de9fa9133a3a