Static Facial Expression In The Wild

Project Overview

Objective

Our goal is to create a big dataset of natural facial expressions, specifically focusing on Static Facial Expression In The Wild, to help AI emotion recognition technology work more accurately and quickly.

Scope

This project involves gathering and labeling facial expressions from different real-life situations to capture the complexity of human emotions.

Facial Expression Recognition Dataset
Facial Expression Recognition Dataset
Facial Expression Recognition Dataset
Facial Expression Recognition Dataset

Sources

  • Surveillance Footage: Using CCTV and public cameras to catch spontaneous facial expressions.
  • Voluntary Submissions: People share their expressions through a secure platform, showing different emotions in different situations.
  • Partnered Public Events: We collaborate with events where people agree to have their expressions recorded.
Facial Expression Recognition Dataset
Facial Expression Recognition Dataset

Data Collection Metrics

  • Total Images Captured: 50,000
  • Surveillance Footage: 30,000
  • Voluntary Submissions: 15,000
  • Partnered Public Events: 5,000

Annotation Process

Stages

  1. Finding Faces: Recognizing and labeling faces in each picture.
  2. Sorting Expressions: Putting expressions into groups like happiness, sadness, surprise, anger, and more.
  3. Measuring Intensity: Rating how strong each expression is to make the dataset more detailed.

Annotation Metrics

  • Images with Pest and Disease Annotations: 15,000
  • Metadata Logging: 15,000
Facial Expression Recognition Dataset
Facial Expression Recognition Dataset
Facial Expression Recognition Dataset
Facial Expression Recognition Dataset

Quality Assurance

Stages

Annotation Review: Our team of experts carefully checks facial expressions to make sure they’re accurate.
Data Cleanup: We regularly clean up the dataset by removing unclear or poorly captured images.
Privacy Protection: We follow strict rules to keep your data safe and private.

QA Metrics

  • Reviewed Annotations: 5,000 (10% of total)

  • Data Cleansing Initiatives

  • Continuous improvement and validation.

Conclusion

In summary, the “Static Facial Expression in the Wild” dataset is a game-changer for improving AI’s grasp of human emotions in everyday situations. With its thorough annotations and detailed data, it paves the way for more accurate and sophisticated emotion recognition systems.

quality dataset

Quality Data Creation

Guaranteed TAT​

Guaranteed TAT

ISO 9001:2015, ISO/IEC 27001:2013 Certified​

ISO 9001:2015, ISO/IEC 27001:2013 Certified

HIPAA Compliance​

HIPAA Compliance

GDPR Compliance​

GDPR Compliance

Compliance and Security​

Compliance and Security

Let's Discuss your Data collection Requirement With Us

To get a detailed estimation of requirements please reach us.

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