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A detector is built in order to recognize faces. To train the detector, a set of face and non-face training images are used. For example:
The face training set consisted of 4916 hand labeled faces scaled and aligned to a base resolution of 24 by 24 pixels. The non-face subwindows used to train the detector come from 9544 images which were manually inspected and found to not contain any faces [1].
So this detector is designed to only detect faces. But you can train the detector to detect eyes, mouth,....
[1] Viola, P., & Jones, M. (2001). Rapid object detection using a boosted cascade of simple features. In Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on (Vol. 1, pp. I-511). IEEE.
