Summary: This paper proposes a camera-based real-time system for building a three-Dimensional (3D) human head model. The proposed system is first trained in a semiautomatic way to locate the user's facial area and is then used to build a 3D model based on the front and profile views of the user's face. This is achieved by directing the user to position his or her face and profile in a highlighted area, which is used to train a neural network to distinguish the background from the face. With a blink from the user, the system is then capable of accurately locating a set of characteristic feature points on the front and profile views of the face, which are used for the adaptation of a generic 3D face model. This adaptation procedure is initialized with a rigid transformation of the model aiming to minimize the distances of the 3D model feature nodes from the calculated 3D coordinates of the 2D feature points. Then, a nonrigid transformation ensures that the feature nodes are displaced optimally close to their exact calculated positions, dragging their neighbors in a way that deforms the facial model in a natural looking manner. A male hair model is created using a 3D ellipsoid, which is truncated and merged with the adapted face model. A cylindrical texture map is finally built from the two image views covering the whole area of the head by exploiting the inherent face symmetry. The final result is a complete, textured model of a specific person's head.