Machine Learning
For general machine learning steps, I first need to get training data to train the network. I took pictures of myself with crying and normal images. Each of them was around 2000 images. These were the training data. The main technique used in my machine learning part is called CNN(Convolutional Neural Network)(11), it is a widely used technique in Deep Learning. By studying given dataset and corresponding labels (cry or not) the network is able to learn the underlying pattern of an image regarding if there is any characteristic of a crying person, for example, the shape of the mouth or shape of the eyes.
Then based on the model that I have. I have a new set of data in order to see whether the training model is accurate. I chose a section of the movie Les Miserables which is a song called I dreamed a dream. This is a super emotional song which the actress cried and sang at the same time. I want to use this song as my final new-data in order to express the idea of how my facial classification read the movie. I saved each frame inside the movie and run them through the model that I had. The result showed which images were crying, which images were normal.
Then I wrote the result in stepper motor’s code from Arduino which illustrated by pushing the syringe forward or backward. If the current image in the video is classified as cry, then it will trigger the syringe from the tears machine to push. So that the dummy head drops water which can be seen as crying.