BodyM Dataset

Stream data with DDA:

from dagshub.streaming import DagsHubFilesystem

fs = DagsHubFilesystem(".", repo_url="https://dagshub.com/DagsHub-Datasets/bodym-dataset")

fs.listdir("s3://amazon-bodym")

Description:

The first large public body measurement dataset including 8978 frontal and lateral silhouettes for 2505 real subjects, paired with height, weight and 14 body measurements. The following artifacts are made available for each subject.

• Subject Height
• Subject Weight
• Subject Gender
• Two black-and-white silhouette images of subject standing in frontal and side pose respectively with full body in view.
• 14 body measurements in cm - {ankle girth, arm-length, bicep girth, calf girth, chest girth, forearm girth, height, hip girth, leg-length, shoulder-breadth, shoulder-to-crotch length, thigh girth, waist girth, wrist girth}

The data is split into 3 sets - Training, Test Set A, Test Set B. For the training and Test-A sets, subjects are photographed and 3D-scanned by in a lab by technicians. For the Test-B set, subjects are scanned in the lab, but photographed in a less-controlled environment with diverse camera orientations and lighting conditions, to simulate in-the-wild image capture. Some subjects have been photographed more than once with different clothing in order to test robustness of the dataset.

Contact:

The first large public body measurement dataset including 8978 frontal and lateral silhouettes for 2505 real subjects, paired with height, weight and 14 body measurements. The following artifacts are made available for each subject.

• Subject Height
• Subject Weight
• Subject Gender
• Two black-and-white silhouette images of subject standing in frontal and side pose respectively with full body in view.
• 14 body measurements in cm - {ankle girth, arm-length, bicep girth, calf girth, chest girth, forearm girth, height, hip girth, leg-length, shoulder-breadth, shoulder-to-crotch length, thigh girth, waist girth, wrist girth}

The data is split into 3 sets - Training, Test Set A, Test Set B. For the training and Test-A sets, subjects are photographed and 3D-scanned by in a lab by technicians. For the Test-B set, subjects are scanned in the lab, but photographed in a less-controlled environment with diverse camera orientations and lighting conditions, to simulate in-the-wild image capture. Some subjects have been photographed more than once with different clothing in order to test robustness of the dataset.

Update Frequency:

None

Managed By:

Amazon

Resources:

1. resource:
   • Description: This S3 bucket has height, weight, gender, measurements and two silhouette images for each type of data
   • ARN: arn:aws:s3:::amazon-bodym
   • Region: us-west-2
   • Type: S3 Bucket

Tags:

computer vision, deep learning

Publication:

1. publication:
   • Title: Human Body Measurement Estimation with Adversarial Augmentation
   • URL: https://www.amazon.science/publications/human-body-measurement-estimation-with-adversarial-augmentation
   • AuthorName: Nataniel Ruiz, Miriam Bellver, Timo Bolkart, Ambuj Arora, Ming C. Lin, Javier Romero and Raja Bala