FPGA implementation of AdaBoost algorithm for detection of face biometrics

At present, most of the high performance arbitrary-shape object detection algorithms are based on statistical methods such as SVM (support vector machine) and AdaBoost method for frontal-view face detection was proposed by Viola in 2001. This method offered impressive accuracy at high speed. Thus, many medical applications requiring biometric and general object detection are good candidates for AdaBoost algorithm. However, in the cases of high-resolution image and real-time video, the algorithm still poses a high computation load that could not be met by average personal computers. In this paper, FPGA (field programmable gate array) design of hardware for a real-time face detection based on AdaBoost algorithm is described. Being fully programmable, hardware design using FPGA offers a much shorter development time and enables a quick verification of DSP algorithms.