Real-time detection with AdaBoost-svm combination in various face orientation

Most of the research has used algorithm AdaBoost-SVM for face detection. However, to our knowledge so far there is no research has been facing detection on real-time data with various orientations using the combination of AdaBoost and Support Vector Machine (SVM). Characteristics of complex and diverse face variations and real-time data in various orientations, and with a very complex application will slow down the performance of the face detection system this becomes a challenge in this research. Face orientation performed on the detection system, that is 90 degrees, 45 degrees, 0 degrees, -45 degrees, and -90 degrees. This combination method is expected to be an effective and efficient solution in various face orientations. The results showed that the highest average detection rate is on the face detection oriented 0 degrees and the lowest detection rate is in the face orientation 90 degrees.