Although our model of a face is a good start, we could make it much more sophisticated. We could model many feature points in order to accurately represent the differences between expressions, such as happiness and sadness. We could consider the third dimension and the camera's perspective. We could identify specific humans and specific cats based on the details of the face or even just the eye. We could train cascades for other species besides humans and cats.
Packt Publishing offers several more advanced OpenCV books with fascinating projects about face analysis. You can consider the following titles:
OpenCV 3 Blueprints offers chapters on facial expression recognition, cascade training, and biometric identification of human faces, eyes, and fingerprints. The code is in C++.
OpenCV for Secret Agents has a chapter on cascade training and biometric identification of human and cat faces. The code is in Python.
Mastering OpenCV with Practical Computer Vision...
