Context
Welcome to the 11k Hands dataset, a collection of 11,076 hand images (1600 x 1200 pixels) of 190 subjects, of varying ages between 18 - 75 years old. Each subject was asked to open and close his fingers of the right and left hands. Each hand was photographed from both dorsal and palmar sides with a uniform white background and placed approximately in the same distance from the camera. There is a record of metadata associated with each image which includes: (1) the subject ID, (2) gender, (3) age, (4) skin color, and (5) a set of information of the captured hand, i.e. right- or left-hand, hand side (dorsal or palmar), and logical indicators referring to whether the hand image contains accessories, nail polish, or irregularities. The proposed dataset has a large number of hand images with more detailed metadata. The dataset is FREE for reasonable academic fair use.
Content
This is a 11k Hands dataset, a collection of 11,076 hand images (1600 x 1200 pixels) of 190 subjects, of varying ages between 18 - 75 years old. Each subject was asked to open and close his fingers of the right and left hands. Each hand was photographed from both dorsal and palmar sides with a uniform white background and placed approximately in the same distance from the camera. There is a record of metadata associated with each image which includes: (1) the subject ID, (2) gender, (3) age, (4) skin color, and (5) a set of information of the captured hand, i.e. right- or left-hand, hand side (dorsal or palmar), and logical indicators referring to whether the hand image contains accessories, nail polish, or irregularities.
Acknowledgements
This dataset is created by the team of researchers who can be cited using:
@article{afifi201911kHands,
title = {11K Hands: gender recognition and biometric identification using a large dataset of hand images},
author = {Afifi, Mahmoud},
journal = {Multimedia Tools and Applications},
doi = {10.1007/s11042-019-7424-8},
url = {https://doi.org/10.1007/s11042-019-7424-8},
year={2019}
}
Inspiration
This dataset can be used to detect age groups; and genders, based on palm and dorsal hand images. For further ideas about the possible works in this project, check the official link where the research and related findings are uploaded.