Facial landmark detection technology identifies the key landmark points on the face from images. The technology detects 64 key points on the face, outlines the facial features, tracks and calculates distances between landmarks.
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Main Function
With our facial landmark detection solutions, specific points on the face can be detected. Based on the coordinates of the person’s nose, mouth, eyes, and other facial features provided by the technology, we are able to detect 64 points on the human face and track their movements. This advanced face detection solution can help enhance other features of our products, such as face identification and face direction detection. It can have separate applications in cases where the coordinates of the facial features are important for the user.
Input
The input is an image.
Output
Output is a list of coordinates of 64 facial landmarks for each face visible in the image.
How Facial Landmarks Are Detected?
The facial landmark detection model is trained on a dataset containing images and their corresponding 64 face landmark points belonging to the nose, mouth, eyes, and the edge of a face. The pre-trained model takes an image as an input and returns the coordinates of the facial landmarks that map to the specific features of the face in the image.
What Are Facial Landmarks Used For?
With the ability to detect key points from a human face, facial landmark detection may be used to monitor driver attention in real time. The system performs an evaluation of the key landmarks on the driver’s face, tracks their movements based on which it estimates whether the driver is paying attention or not.
Facial landmark detection techniques may also be applied for measuring students’ level of engagement during online lessons. The technology analyzes facial landmarks deriving several features relating to eye movements and blink patterns, and provides relevant information for measuring student engagement levels.
What Is the Difference Between Face Detection and Facial Landmark Detection?
Face detection extracts and identifies the presence of human faces in an image or video. Face detection algorithms often start by searching for human eyes. After detecting the eyes, the algorithm then tries to detect facial features, including the eyebrows, nose, iris, and mouth. Once the algorithm concludes the detection of these facial features, it goes through the testing process to verify that it has actually detected a face.
The facial landmark detection model focuses on detecting a specific face region and a landmark. The system detects and accurately locates the landmarks on the person’s eyebrows, eye corners, nose, chin, mouth corners, and other facial features. Facial landmark detection can help recognize face position, facial expressions and extracting points on the face.
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Our API has simple integration and is easy to use. You just need to sign up, test the API, copy the code snippet into your website to integrate it with your services, and you are ready to go.
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For example
[
{
'landmarks': [
[354.0, 328.0], [353.0, 343.0],
[354.0, 361.0], [358.0, 376.0],
[363.0, 393.0], [369.0, 411.0],
[383.0, 425.0],[401.0, 437.0],
[426.0, 445.0], [451.0, 437.0],
[465.0, 427.0], [473.0, 420.0],
[483.0, 408.0], [491.0, 396.0],
[498.0, 385.0], [506.0, 370.0],
[511.0, 355.0], [383.0, 316.0],
[398.0, 313.0], [411.0, 313.0],
[423.0, 318.0], [431.0, 321.0],
[473.0, 326.0], [483.0, 326.0],
[491.0, 325.0], [501.0, 328.0],
[510.0, 335.0], [451.0, 351.0],
[450.0, 365.0], [448.0, 380.0],
[448.0, 391.0], [428.0, 396.0],
[436.0, 398.0], [445.0, 398.0],
[451.0, 396.0], [456.0, 395.0],
[396.0, 336.0], [406.0, 335.0],
[416.0, 336.0], [425.0, 341.0],
[416.0, 343.0], [405.0, 341.0],
[470.0, 346.0], [480.0, 343.0],
[490.0, 345.0], [495.0, 348.0],
[488.0, 351.0], [478.0, 350.0],
[410.0, 410.0], [423.0, 410.0],
[436.0, 410.0], [441.0, 410.0],
[448.0, 408.0], [456.0, 410.0],
[463.0, 410.0], [455.0, 416.0],
[446.0, 421.0], [440.0, 421.0],
[430.0, 421.0], [421.0, 416.0],
[411.0, 410.0], [433.0, 413.0],
[441.0, 413.0], [448.0, 413.0],
[461.0, 410.0], [448.0, 413.0],
[440.0, 413.0], [431.0, 413.0]
]
},
{
'landmarks': [
[54.0, 28.0], [53.0, 43.0],
[354.0, 361.0], [358.0, 376.0],
[363.0, 393.0], [369.0, 411.0],
[383.0, 425.0], [401.0, 437.0],
[426.0, 445.0], [451.0, 437.0],
[465.0, 427.0], [473.0, 420.0],
[483.0, 408.0], [491.0, 396.0],
[498.0, 385.0], [506.0, 370.0],
[511.0, 355.0], [383.0, 316.0],
[398.0, 313.0], [411.0, 313.0],
[423.0, 318.0], [431.0, 321.0],
[473.0, 326.0], [483.0, 326.0],
[491.0, 325.0], [501.0, 328.0],
[510.0, 335.0], [451.0, 351.0],
[450.0, 365.0], [448.0, 380.0],
[448.0, 391.0], [428.0, 396.0],
[436.0, 398.0], [445.0, 398.0],
[451.0, 396.0], [456.0, 395.0],
[396.0, 336.0], [406.0, 335.0],
[416.0, 336.0], [425.0, 341.0],
[416.0, 343.0], [405.0, 341.0],
[470.0, 346.0], [480.0, 343.0],
[490.0, 345.0], [495.0, 348.0],
[488.0, 351.0], [478.0, 350.0],
[410.0, 410.0], [423.0, 410.0],
[436.0, 410.0], [441.0, 410.0],
[448.0, 408.0], [456.0, 410.0],
[463.0, 410.0], [455.0, 416.0],
[446.0, 421.0], [440.0, 421.0],
[430.0, 421.0], [421.0, 416.0],
[411.0, 410.0], [433.0, 413.0],
[441.0, 413.0], [448.0, 413.0],
[461.0, 410.0], [448.0, 413.0],
[440.0, 413.0], [431.0, 413.0]
]
}
]
