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In today’s world, video calls have become an essential part of how we connect-whether for work, education, or socializing. Yet, one common challenge remains: lack of natural eye contact. This subtle but crucial aspect of communication often feels missing, making conversations less engaging and authentic. That’s why I’m excited to share my latest project: Gaze Correction Camera - an innovative system that uses computer vision and deep learning to adjust your eye gaze direction in real-time during video calls. By intelligently correcting where your eyes appear to be looking, it creates a more natural and comfortable eye contact experience for everyone on the call. What does this mean for you? More engaging and trustworthy virtual meetings Improved communication and connection Seamless integration with your existing camera setup How it works: The system leverages advanced facial landmark detection and warping-based convolutional neural networks to subtly shift your gaze without interrupting the video stream. It runs efficiently in real-time on macOS, requiring only a standard webcam and GPU resources. Interested in the tech behind it? The project is open-source and built with Python 3.12+, using tools like Poetry for dependency management and CMake for building essential libraries. You can find detailed installation instructions, configuration options, and usage guidelines on the GitHub repo.
In today’s world, video calls have become an essential part of how we connect-whether for work, education, or socializing. Yet, one common challenge remains: lack of natural eye contact. This subtle but crucial aspect of communication often feels missing, making conversations less engaging and authentic.
That’s why I’m excited to share my latest project: Gaze Correction Camera - an innovative system that uses computer vision and deep learning to adjust your eye gaze direction in real-time during video calls. By intelligently correcting where your eyes appear to be looking, it creates a more natural and comfortable eye contact experience for everyone on the call.
What does this mean for you?
- More engaging and trustworthy virtual meetings
- Improved communication and connection
- Seamless integration with your existing camera setup
How it works:
The system leverages advanced facial landmark detection and warping-based convolutional neural networks to subtly shift your gaze without interrupting the video stream. It runs efficiently in real-time on macOS, requiring only a standard webcam and GPU resources.
Interested in the tech behind it?
The project is open-source and built with Python 3.12+, using tools like Poetry for dependency management and CMake for building essential libraries. You can find detailed installation instructions, configuration options, and usage guidelines on the GitHub repo.
