Gesture Recognition - 10,000+ videos

The Gesture Recognition Dataset is a comprehensive collection of over 10,000 high-resolution videos showcasing individuals performing five distinct hand gestures:

1. “One”
2. “Four”
3. “Small”
4. “Fist”
5. “Me”

This dataset is ideal for advancing research in gesture recognition, focusing on applications like sign language interpretation, gesture-controlled devices, and human-computer interaction systems. By including a diverse range of participants, the dataset enables the development of robust and versatile AI models.

Dataset Features

• Extensive Video Collection:
  High-quality videos captured under optimal lighting conditions ensure clear visibility of hand gestures and movements.

• Diverse Participants:
  Includes individuals with varying hand shapes, sizes, and movements, enhancing the generalization of AI models.

• Applications:
  Designed for gesture recognition systems, pattern recognition, and classification tasks in AI-driven technologies.

Key Details

• Use Cases:

  • Develop gesture-controlled interfaces for smart devices and virtual reality.
  • Train AI models for real-time sign language interpretation systems.
  • Research and improve hand gesture recognition (HGR) systems in fields like gaming, robotics, and augmented reality.

• Optimal Data Quality:
  Each video is recorded in high resolution and consistent lighting conditions, ensuring the highest data quality for computer vision tasks.

• Research and Development:
  Enables researchers and developers to explore innovative recognition algorithms and enhance machine learning techniques for gesture detection.

This dataset is sourced from Kaggle.