Introduction
Welcome to the Middle Eastern Human Facial Images Dataset, meticulously curated to enhance face recognition models and support the development of advanced biometric identification systems, KYC models, and other facial recognition technologies.
Facial Image Data
This dataset comprises over 1500 Middle Eastern individual facial image sets, with each set including:
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Selfie Images:
5 different high-quality selfie images per individual.
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ID Card Images:
2 high-quality images of the individual’s face from different ID cards.
Diversity and Representation
The dataset includes contributions from a diverse network of individuals across Middle Eastern countries.
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Geographical Representation:
Participants from Middle Eastern countries, including Egypt, Jordan, Suadi Arabia, UAE, Tunisia, and more.
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Participant Profile:
Participants range from 18 to 70 years old, representing both males and females in a 60:40 ratio, respectively.
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File Format:
The dataset contains images in JPEG and HEIC file format.
Quality and Conditions
To ensure high utility and robustness, all images are captured under varying conditions:
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Lighting Conditions:
Images are taken in different lighting environments to ensure variability and realism.
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Backgrounds:
A variety of backgrounds are available to enhance model generalization.
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Device Quality:
Photos are taken using the latest mobile devices to ensure high resolution and clarity.
Metadata
Each facial image set is accompanied by detailed metadata for each participant, including:
•Unique Identifier
•File Name
•Age
•Gender
•Country
•Demographic Information
•File Format
This metadata is essential for training models that can accurately recognize and identify faces across different demographics and conditions.
Usage and Applications
This facial image dataset is ideal for various applications in the field of computer vision, including but not limited to:
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Facial Recognition Models:
Improving the accuracy and reliability of facial recognition systems.
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KYC Models:
Streamlining the identity verification processes for financial and other services.
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Biometric Identity Systems:
Developing robust facial biometric identification solutions.
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Age Prediction Models:
Training models to accurately predict the age of individuals based on facial features.
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Generative AI Models:
Training generative AI models to create realistic and diverse synthetic facial images.
Secure and Ethical Collection
•Data was securely stored and processed within our platform, ensuring data security and confidentiality.
•The biometric data collection process adhered to strict ethical guidelines, ensuring the privacy and consent of all participants.
•All participants were informed of the purpose of collection and potential use of the data, as agreed through written consent. Also, demographic-related regulations are kept in mind.
Updates and Customization
We understand the evolving nature of AI and machine learning requirements. Therefore, we continuously add more assets with diverse conditions to this off-the-shelf facial image dataset.
•Customization & Custom Collection Options:
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Background Conditions:
Specific conditions upon request, like indoor or outdoor
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Lighting Condition:
Different lighting conditions can be achieved.
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Capture Time:
Variation can be achieved by capturing images at different times of day like morning, afternoon, evening, or night as per requirement.
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Resolution:
Custom collection as per requirement.
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Annotation:
Custom annotations like facial landmarks, facial boundaries, semantics, or any other application-specific annotations can be done upon request.
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Device-specific Collection:
Data can be collected from specific devices with specific brands or operating systems.
License
This facial image training dataset is created by FutureBeeAI and is available for commercial use.