Real-time face detection on reconfigurable device
Mooseop Kim, Seungwan Han · 2013
This paper presents an efficient hardware architecture for a real-time face detection system using a reconfigurable logic device. The proposed architecture is based on AdaBoost learning algorithm with Haar-like features and it aims to apply to a reconfigurable device. The proposed system was verified by the RTL functional simulation and tested the same input images on the OpenCV program for a fair verification of the functionality. The experimental results show that the processing time for a 320×240 pixel image is 42 frames per second with the 100MHz.