GPU加速人脸检测

Jiangang Kong, Yangdong Deng
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引用次数: 37

摘要

最近,多核图形处理器单元(gpu)正在为通用计算应用程序提供令人印象深刻的能力。由于其高内存带宽和计算吞吐量,gpu通常可以显着加速许多应用程序。本文提出了一种基于Viola-Jones[5]的人脸检测系统的CPU-GPU协同实现。实验结果表明,我们的人脸检测器在GTX280显卡上运行,与在Intel酷睿2双核处理器上运行的CPU相比,可以实现超过20倍的加速,同时保持完全相同的检测质量。我们还展示了我们的实现在图像大小方面提供了良好的可伸缩性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GPU accelerated face detection
Recently many-core graphic processor units (GPUs) are delivering impressive power for general purpose computing applications. Thanks to their high memory bandwidth and computing throughput, GPUs could often significantly accelerate many applications. In this paper, we present a CPU-GPU cooperative implementation for a Viola-Jones [5] based face detection system. The experiment results show that our face detector running on a GTX280 graphics card could achieve an over 20X speed-up compared with the CPU equivalent on an Intel core 2 duo processor, while maintaining exactly the same detection quality. We also show that our implementation offers good scalability in terms of image size.
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