【摘要】 针对目前大多嵌入式人脸检测系统因资源限制而导致的软件方式实现速度较慢的问题,提出利用软硬件协同的方法来加速人脸检测。在Zynq-7000平台的基础上,使用C语言实现了基于AdaBoost级联分类器的人脸检测算法,并测试了各个模块的运行时间。结合算法实现的具体过程及其繁复程度给出了硬件加速方案。将检测算法计算量大而多的部分转移到硬件部分进行优化加速,在Zynq-7000平台上实现了软硬件协同的人脸检测,最后给出了相应模块的加速结果。更多还原

【Abstract】 Compared with the desktops,there are mainly two problems of the embedded face detection systems,which are less resource and slower speed.Here we put forward the method of using software-hardware codesign to accelerate the face detection process.Firstly,we implemented the face detection algorithm on platform Zynq-7000 with C programming language,which is based on AdaBoost cascade classifiers.Then,the performace of the algorithm was tested with Xilinx SDK.Afterwards,a software-hardware partion strategy of the algorithm was raised for acceleration.By transplanting the most computational part of the algorithm to the hardware implementation,we realized the software-hardware codesign of the face detection system on platform Zynq-7000.At last,we presented the acceleration results of two hardware modules,and summarized the related work.更多还原