Native American Children Facial Image Dataset

This dataset consists of images of children below 18 years from Native American countries. The dataset also includes extensive metadata.

About This OTS Dataset

Introduction

Welcome to the Native American Child Faces Dataset, meticulously curated to enhance face recognition models and support the development of advanced biometric identification systems, child identification models, and other facial recognition technologies.

Facial Image Data

This dataset comprises over 3,000 child image sets, divided into participant-wise sets with each set including:

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Facial Images: 15 different high-quality images per child.

Diversity and Representation

The dataset includes contributions from a diverse network of children across Native American countries:

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Geographical Representation: Participants from Native American countries, including USA, Canada, Mexico and more.

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Demographics: Participants are children under the age of 18, representing both males and females.

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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:

•Participant Identifier

•File Name

•Age

•Gender

•Country

•Demographic Information

•File Format

This metadata is essential for training models that can accurately recognize and identify children's 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 biometric identification solutions.

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Child Identification Models: Training models to accurately identify children in various scenarios.

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Age Prediction Models: Training models to accurately predict the age of minors 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

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Data Security: Data was securely stored and processed within our platform, ensuring data security and confidentiality.

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Ethical Guidelines: The biometric data collection process adhered to strict ethical guidelines, ensuring the privacy and consent of all participants’ guardians.

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Participant Consent: The guardians were informed of the purpose of collection and potential use of the data, as agreed through written consent.

Updates and Customization

We understand the evolving nature of AI and facial recognition model 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 Conditions: 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.