Face detection is a primary step in many applications such as face recognition, video surveillance, human computer interface, and expression recognition. Many existing detection techniques suffer under scale variation, pose variation (frontal vs. profile), illumination changes, and complex backgrounds. In this paper, we present a robust and efficient method for face detection in color images. Skin color segmentation and edge detection are employed to separate all non-face regions from the candidate faces. Primitive shape features are then used to decide which of the candidate regions actually correspond to a face. The advantage of this method is its ability to achieve a high detection rate under varying conditions (pose, scale,...) with low computational cost. © 2007 Springer-Verlag Berlin Heidelberg.
|Journal||Advances in Soft Computing|
|Publication status||Published - 1 Dec 2007|
Haj, M. A., Amato, A., Roca, X., & Gonzàlez, J. (2007). Face detection in color images using primitive shape features. Advances in Soft Computing, 45, 179-186. https://doi.org/10.1007/978-3-540-75175-5_23