Facial Keypoint Detection is the first project in Udacity's Computer Vision Nanodegree program. This project combines knowledge of computer vision techniques and deep learning architectures to build a facial keypoint detection system. Facial keypoints include points around the eyes, nose, and mouth on a face and are used in many applications. These applications include: facial tracking, facial pose recognition, facial filters, and emotion recognition. The completed project code is able to look at any image, detect faces, and predict the locations of facial keypoints on each face.
The project is broken up into a few main parts in four Python notebooks.
Notebook 1 : Loading and Visualizing the Facial Keypoint Data
Notebook 2 : Defining and Training a Convolutional Neural Network (CNN) to Predict Facial Keypoints
Notebook 3 : Facial Keypoint Detection Using Haar Cascades and your Trained CNN
Notebook 4 : Fun Filters and Keypoint Uses
LICENSE: This project is licensed under the terms of the MIT license.