Face Detection Using Discrete Gabor Jets and a Probabilistic Model of Colored Image Patches
Face detection allows to recognize and detect human faces and provides information about their location in a given image. Many applications such as biometrics, face recognition, and video surveillance employ face detection as one of their main modules. Therefore, improve- ment in the performance of existing face detection systems and new achievements in this ﬁeld of research are of signiﬁcant importance. In this paper a hierarchical classiﬁcation approach for face detection is presented. In the ﬁrst step, discrete Gabor jets (DGJ) are used for ex- tracting features related to the brightness information of images and a preliminary classiﬁcation is made. Afterwards, a skin detection algo- rithm, based on modeling of colored image patches, is employed as a post-processing of the results of DGJ-based classiﬁcation. It is shown that the use of color efficiently reduces the number of false positives while maintaining a high true positive rate. A comparison is made with the OpenCV implementation of the Viola and Jones face detector and it is concluded that higher correct classiﬁcation rates can be attained using the proposed face detector.