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基于GPU的PCA人脸识别系统设计 被引量：2

Design of PCA Face Recognition System Based on GPU
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摘要 针对实际人脸识别系统需要满足实时性的应用需要,探讨了在图形处理器(GPU)硬件架构基础上的基于主成分分析(PCA)人脸识别系统设计与实现.结合统一计算设备架构(CUDA)的计算平台,通过将算法中耗时长、适合并行的部分过程映射到GPU上并行执行改进系统的加速实现.实验结果表明:相对于基于CPU平台的串行实现,基于GPU的实现在整体上能够获得约5倍的加速,而两个执行并行的模块能分别获得最大20倍和30倍的加速. Aiming to the application requirement of the real-time facial recognition systems,the implementation of principle component analysis（ PCA） based face recognition in graphics processing unit（ GPU） was exploited. With Compute Unified Device Architecture（ CUDA） computational platform,some time-consuming modules are mapped to GPUs for parallel processing for acceleration. Experimental results demonstrate that,when comparing to the CPU-based serial implementation,the GPU-based realization could achieve about 5 times speedup in all with an utmost 20-30 times speedup for the two parallel processing modules.
作者 熊承义 李靓琦 高志荣 周城
机构地区 中南民族大学电子信息工程学院智能无线通信湖北省重点实验室 中南民族大学计算机科学学院
出处 《中南民族大学学报（自然科学版）》 CAS 北大核心 2015年第2期85-90,共6页 Journal of South-Central University for Nationalities：Natural Science Edition
基金 国家自然科学基金资助项目(61471400 61201268) 湖北省自然科学基金资助项目(2013CFC118) 中央高校基本科研业务费专项(CZW14018)
关键词 主成分分析 人脸识别 图形处理器 统一计算设备架构 PCA face recognition GPU CUDA
分类号 TN919.8 [电子电信—通信与信息系统]
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参考文献9

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二级参考文献17

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中南民族大学学报（自然科学版）
2015年 第2期

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