Faces are an identifying feature of human anatomy. Strictly speaking, many animals also have faces, but that is less relevant for most practical applications. Face detection tries to find (rectangular) areas in an image that represent faces. Face detection is a type of object detection, because faces are a type of object.
Most face detection algorithms are good at detecting clean fron-facing faces because most training images fall in that category. Tilted faces, bright lights, or noisy images may cause problems for face detection. It is possible to deduce age, gender, or ethnicity (for instance, the presence of epicanthic folds) from a face, which of course is useful for marketing.
A possible application could be analyzing profile pictures on social media sites. OpenCV uses a Haar feature-based cascade classifiers system to detect faces. The system is also named the Viola–Jones object detection framework after its inventorsr who proposed it in 2001.
The algorithm...