Face detection based on Adaboost cascade algorithms
Ping Bi · Journal of Xi'an University of Post and Telecommunications · 2008
In this paper,a face detection algorithm based on a Adaboost cascade algorithms is studied in detail.Constructs a cascade classification system,by a number of weak classifier to build a strong classifier,and then from a number of strong classifier,build a stacked classification system eventually. By increasing the cascading series classifier to reduce the face error rate and increasing the number of classifier to increase the face detection rate,making the stacked classifier to have the expanding upgrading capacity.The simulation results proved that the success of this strategy can reduce the error rate and calculation time significantly,and can improve the detection performance.It can apply to real-time video face detection.