摘要: 实现一个硬件人脸检测系统,该系统工作频率为70 MHz,能够检测一幅256×256的图像中任意位置、任意大小和任意数目的人脸,检测速度为每秒35帧。系统的检测精度为85%,误检率为1.5×10-6。为实现高速人脸检测,在硬件系统架构上做出如下3点创新:实现积分图像和积分平方图像的硬件实时计算,弱分类器特征值计算的深流水线实现,采用并行多内存组织结构。
关键词:
硬件人脸检测,
人脸识别,
Adaboost算法
Abstract: This paper presents a hardware implementation of face detection system that can detect any number of faces with any size at any position in a 256×256 image, at a speed of 35 fps when the FPGA works at 70 MHz. The detection system can achieve a detection rate of 85% with a false alarm rate of 1.5×10-6. To achieve high speed face detection, three contributions are made in the hardware architecture: real-time hardware implementation of the calculations of integral image and integral squared image, deep pipeline architecture of weak classifier implementation, and parallel multi-memory organization.
Key words:
hardware face detection,
face recognition,
Adaboost
中图分类号:
唐 奇;苏光大. 基于Adaboost算法的硬件实时人脸检测[J]. 计算机工程, 2008, 34(7): 248-250.
TANG Qi; SU Guang-da. Real-time Hardware Face Detection Based on Adaboost Algorithm[J]. Computer Engineering, 2008, 34(7): 248-250.