This project focuses on accurately estimating the head pose in real-time, and it’s packed with powerful features and improvements to ensure efficient and seamless performance. Whether it’s for AR/VR applications, attention tracking, or even driver monitoring systems, head pose estimation plays a crucial role in numerous industries.

🚀 Link to open-source project on github: https://github.com/yakhyo/head-pose-estimation 🔗

💡 Main Highlights of the Project:

  • ✨ Refined Code for Seamless Head Pose Estimation
    The code has been optimized for performance, ensuring smooth and real-time head pose estimation across various environments.

  • 🏗 Added Powerful Backbones like ResNet, MobileNet v2/v3
    With the inclusion of ResNet and MobileNet v2/v3 backbones, the model delivers high accuracy and efficiency, making it suitable for mobile and edge devices.

  • 👤 Integrated Face Detection with SCRFD
    SCRFD has been incorporated into the pipeline for fast and accurate face detection, which is crucial for reliable head pose estimation.

🔥 Why This Project Matters?

With the growing importance of real-time applications in areas such as augmented reality, attention monitoring, and safety systems (like in automotive industries), the need for accurate head pose estimation is more relevant than ever. By integrating robust backbones like ResNet and MobileNet, and combining them with efficient face detection (SCRFD), this project delivers a balance of speed, accuracy, and practicality for both desktop and mobile platforms.

The flexibility and lightweight nature of the models also make them ideal for deployment on mobile devices without sacrificing performance.

📈 Future Prospects:

As this project evolves, there are many opportunities for improvement, including:

  • Further optimization for even lower-latency scenarios on mobile devices.
  • Expanding the dataset to improve performance in diverse conditions.
  • Exploring more advanced backbones to push the boundaries of accuracy and speed.

Feel free to check out the project, share your thoughts, or contribute to its growth. I’m always open to feedback and collaboration! 💬