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Facial Keypoint Detection

This project will be all about defining and training a convolutional neural network to perform facial keypoint detection, and using computer vision techniques to transform images of faces.

Facial keypoints (also called facial landmarks) are the small magenta dots shown on each of the faces in the image above. In each training and test image, there is a single face and 68 keypoints, with coordinates (x, y), for that face. These keypoints mark important areas of the face: the eyes, corners of the mouth, the nose, etc. These keypoints are relevant for a variety of tasks, such as face filters, emotion recognition, pose recognition, and so on. Here they are, numbered, and you can see that specific ranges of points match different portions of the face.

facial kepoints
keypoints landmarks

For this task, CNN(Convolutional Neural Network) is used. It is recommended to add multiple convolutional layers and things like dropout layers that may prevent overfitting. It is also recommended to look at literature on keypoint detection, such as this paper, to help you determine the structure of your network.

michelle_detected

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