Simple Face Recognition
A face recognition network can be trained in such a way that the Euclidean distance in the embedding feature space directly corresponds to face similarity. Using the embedding as facial descriptors, we can implement a simple face recognition algorithm without the need to train a new model.
Here is a small sample of a set of images from a family of five.
Compute the facial descriptors for each person.
You can use FeatureSpacePlot to visualize the descriptors in clusters.
Use Classify to perform classification in the feature space.
Apply the classifier on a new image.
Visualize the classification on top of the test image.
Try the classifier on an image taken at a different point in time.