基于CUDA的实时人脸识别系统

通过对人脸识别系统的2个关键部分的优化，实现一种快速高效的人脸识别系统。在面部检测阶段改进图像积分的并行算法；在面部识别阶段尝试算法的并行化，并且把测试阶段的一部分进行了并行化。与传统的CPU识别程序相比，CUDA平台改进程序可在面部检测阶段实现22.42倍的加速比，在面部识别阶段实现1668.56倍的加速比。实验数据表明，本文提出的人脸识别系统具有很高的实时性能。

CUDA-based Real-time Face Recognition System

Through the optimization of the two important part of face recognition system, we proposed a CUDA-based real-time face recognition system. In the face detection phase with Viola-Jones cascade classifier, we implemented and improved novel parallel methodologies of image integral, calculation scan window processing and the amplification and correction of classifiers. In the face recognition phase, we explored the parallelizing of the algorithm and parallelized some part of the testing phase.  In comparison with traditional CPU program, the proposed approach running on an NVIDIA GTX 570 graphics card could respectively achieve 22.42 times speedup in detection phase and 1668.56 times speedup in recognition phase. The recognition speed will increase until it reaches the hardware resource limit. The experimental results demonstrate that the system achieves a good real-time performance.