In this document, we address the problem of multiview face detection. This work extends the frontal face detection system developed at the IDIAP Research Institute to multiview face detection. The main state-of-the art techniques are reviewed and a novel architecture is presented, based on a pyramid of detectors that are trained for different views of faces. The proposed approach robustly detects faces rotated up to -67.5 degree in the image plane and up to -90 degree out of the image plane. The system is real-time and achieves high performances on benchmark test sets, comparable to some state-of-the-art approaches.