Title :
GPU accelerated face detection
Author :
Kong, Jiangang ; Deng, Yangdong
Author_Institution :
Inst. of Microelectron., Tsinghua Univ., Beijing, China
Abstract :
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 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.
Keywords :
computer graphic equipment; coprocessors; face recognition; object detection; GPU accelerated face detection; GTX280 graphics; Intel core 2 duo processor; Viola-Jones based face detection system; general purpose computing; many-core graphic processor units; Acceleration; Classification algorithms; Face; Face detection; Graphics processing unit; Instruction sets; Real time systems;
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2010 International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-7047-1
DOI :
10.1109/ICICIP.2010.5564978