African Facial Expression Image Dataset

This dataset features facial images of African individuals displaying distinct expressions like happy, sad, angry, shocked, neutral, etc. The dataset is accompanied by rich metadata, making it ideal for emotion recognition and facial expression analysis models.

About This OTS Dataset

Introduction

Welcome to the African Facial Expression Image Dataset, curated to support the development of advanced facial expression recognition systems, biometric identification models, KYC verification processes, and a wide range of facial analysis applications. This dataset is ideal for training robust emotion-aware AI solutions.

Facial Expression Data

The dataset includes over 2000 high-quality facial expression images, grouped into participant-wise sets. Each participant contributes:

•

Expression Images: 5 distinct facial images capturing common human emotions: Happy, Sad, Angry, Shocked, and Neutral

Diversity & Representation

•

Geographical Coverage: Individuals from African countries including Kenya, Malawi, Nigeria, Ethiopia, Benin, Somalia, Uganda, and more

•

Demographics: Participants aged 18 to 70 years, with a gender distribution of 60% male and 40% female

•

File Formats: All images are available in JPEG and HEIC formats

Image Quality & Capture Conditions

To ensure generalizability and robustness in model training, images were captured under varied real-world conditions:

•

Lighting Conditions: Natural and artificial lighting to represent diverse scenarios

•

Background Variability: Indoor and outdoor backgrounds to enhance model adaptability

•

Device Quality: Captured using modern smartphones to ensure clarity and consistency

Metadata

Each participant's image set is accompanied by detailed metadata, enabling precise filtering and training:

•Unique Participant ID

•File Name

•Age

•Gender

•Country

•Facial Expression Label

•Demographic Information

•File Format

This metadata helps in building expression recognition models that are both accurate and inclusive.

Use Cases & Applications

This dataset is ideal for a variety of AI and computer vision applications, including:

•

Facial Expression Recognition: Improve accuracy in detecting emotions like happiness, anger, or surprise

•

Biometric & Identity Systems: Enhance facial biometric authentication with expression variation handling

•

KYC & Identity Verification: Validate facial consistency in ID documents and selfies despite varied expressions

•

Generative AI Training: Support expression generation and animation in AI-generated facial images

•

Emotion-Aware Systems: Power human-computer interaction, mental health assessment, and adaptive learning apps

Secure & Ethical Collection

•

Data Security: All data is securely processed and stored on FutureBeeAI’s proprietary platform

•

Ethical Standards: Collection followed strict ethical guidelines ensuring participant privacy and informed consent

•

Informed Consent: All participants were made aware of the data use and provided written consent

Dataset Updates & Customization

To support evolving AI development needs, this dataset is regularly updated and can be tailored to project-specific requirements. Custom options include:

•

Background Settings: Indoor, outdoor, or controlled environment images

•

Lighting Variations: Custom lighting setups (e.g., daylight, low-light)

•

Capture Time: Morning, afternoon, evening, or night-specific captures

•

Image Resolution: Custom image resolution upon request

•

Annotations: Facial landmarks, emotion intensity scores, or semantic labels

•

Device-Specific Collection: Data captured from specific mobile devices or OS platforms