Facial Landmark Detection
Last updated
Last updated
Each health assessment within the BitDoctor.ai platform requires precise facial landmark detection. While each study may have unique needs, the system currently focuses on 15 core facial landmarks for most applications. These points are crucial for identifying the regions of interest, enabling accurate arterial blood-flow extraction for health data analysis.
In addition to the core landmarks, 44 visual animation points are used for enhancing the user experience through seamless interface rendering. These points, while primarily aesthetic, do not influence the quality of health measurements but ensure an engaging and user-friendly interaction with the platform.
The 15 core facial data points used by BitDoctor.ai are highlighted in the image with red dots, each labeled with a corresponding identifier. These points are essential for accurate health data extraction, as they represent the specific regions required for arterial blood-flow analysis.
The black box represents the detected face rectangle, which serves as the foundation for BitDoctor.ai's advanced Extraction Library to map these critical facial points. This precise detection ensures that health metrics are both accurate and reliable, supporting the platform's mission of delivering early disease detection and proactive healthcare solutions.
In addition to providing the black face bounding box, the 15 required point names are:
3.1, 3.2, 3.3, 3.4, 3.7, 3.8, 3.11, 3.12, 8.1, 8.2, 8.3, 8.4, 9.1, 9.2, 9.3
BitDoctor.ai uses 44 animation points to construct the visual contours of the face seen by end users. Unlike core measurement points, these animation points are designed for aesthetic purposes and don’t require high accuracy. While slight inaccuracies may occur, such as group 13 series drifting from the face edge, these do not affect health data quality and serve only to enhance visual.
The 44 points used for visual animation include:
2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 4.1, 4.2, 4.3, 4.4, 8.10, 8.5, 8.6, 8.7, 8.8, 8.9, 9.12, 9.15, 9.4, 9.5, 12.1, 12.11, 12.12, 12.7, 12.8, 13.10, 13.11, 13.12, 13.13, 13.14, 13.15, 13.16, 13.17, 13.3, 13.4, 13.5, 13.6, 13.7, 13.8, 13.9, 14.1, 14.2
