Abstract
Artificial Intelligence has gradually become the mainstream in the detection algorithms because of its powerful feature extraction ability and adaptive ability. However, how to guarantee the accuracy and speed is still a huge challenge in the field of depth measurement. We implement face mesh from media pipe (module) which is developed by google. Media Pipe Face Mesh is a face geometry solution that estimates 468 3D face landmarks in real-time even on mobile devices. It employs machine learning (ML) to infer the 3D surface geometry, requiring a single camera input without the need for a dedicated depth sensor. Using face mesh, we take points from face and depth is measured. This makes project more accurate and speed. In our project we measure real time 3D depth, using these we make our text flexible with depth measured from webcam. When we move closer to our webcam text size reduces, and when we go far from webcam, text size is enhanced, which is accordance to the convenience to our end users. When we implement this in real life, end users can see the captions comfortably from any place they are watching the screen only. Keywords: OpenCV, Mediapipe , FaceMesh, Windows, Python.
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