基于FPGA的高精度人脸检测加速

High Accuracy Face Detection Acceleration Based on FPGA

针对人脸检测对高实时性的要求,系统测试了Viola-Jone算法的数据表示(定点/浮点)对检测假阳性和假阴性的影响,检测在逐步降低数据精度的基础上进行。最后在对定点检测评价的基础上提出了一种基于CPU和FPGA混合执行Viola-Jone算法的框架,充分利用FPGA的并行性,对定点表示的Viola-Jone算法进行显著加速处理,极大的提高了人脸检测速度。

Aiming at the high real-time requirement of face detection,this paper systematically tests the influence of the data representation(fixed-point/floating-point)of Viola-Jone algorithm on the detection of false positive and false negative,and detects the face on the basis of gradually reducing the accuracy of the data.Based on the evaluation of fixed-point detection,a frame of Viola-Jone algorithm based on CPU and FPGA is proposed,which makes full use of the parallelism of FPGA to speed up the Viola-Jone algorithm.As a result,the speed of face detection is greatly improved.