Facial Recognition Dataset – Labeled Faces in the Wild
Project Overview:
Objective
The aim was to create a dataset that makes facial recognition systems better at recognizing faces accurately and quickly. This dataset includes a variety of real-life facial images to achieve this goal.
Scope
We collected and marked many different facial expressions and situations, paying attention to how they’re used in real life. The project recorded various facial characteristics from different groups of people to make sure the dataset works well in different situations.
Sources
- Real Human Interactions: We took pictures of people showing natural facial expressions in different situations. These people were of different ages and came from different cultural backgrounds.
- Simulated Scenarios: We included photos of actors acting out different emotions to add more variety to the dataset.
Data Collection Metrics
- Total Data Collected: 40,000 images of facial expressions.
- Data Annotated for ML Training: 50,000 images.
Annotation Process
Stages
- Expression Categories: We sorted expressions into simple emotions like happiness, sadness, fear, and surprise.
- Intensity Rating: Each picture was given a score to show how strong the emotion is, helping to understand it better.
- Demographic Tags: We added details about the people in the pictures, like age and gender, to make the data more useful for different facial recognition purposes.
Annotation Metrics
Annotated Expressions: 50,000
Categorization Labels: 50,000
Intensity Labels: 40,000
Quality Assurance
Stages
Continuous Model Testing: We keep checking our models regularly to make them more accurate.
Privacy Rules: We followed strict privacy laws, making sure all data we collected was with permission and made anonymous.
Improvement Process: We used feedback from the models to keep making the dataset and training methods better.
QA Metrics
- Expression Recognition Accuracy: 95%
- Intensity Detection Accuracy: 92%
- Privacy Compliance: 100%
Conclusion
The “Labeled Faces in the Wild” dataset has greatly improved facial recognition technology. It provides detailed information about different human expressions, which helps in making advances in AI-based emotional understanding and interactive systems.
Quality Data Creation
Guaranteed TAT
ISO 9001:2015, ISO/IEC 27001:2013 Certified
HIPAA Compliance
GDPR Compliance
Compliance and Security
Let's Discuss your Data collection Requirement With Us
To get a detailed estimation of requirements please reach us.