J4 ›› 2011, Vol. 38 ›› Issue (3): 76-82.doi: 10.3969/j.issn.1001-2400.2011.03.013

• 研究论文 • 上一篇    下一篇

一种用于人脸检测SoC中的加速协处理器设计

焦继业1;穆荣2;郝跃1
  

  1. (1. 西安电子科技大学 宽禁带半导体材料与器件教育部重点实验室,陕西 西安  710071;
    2. 西安科技大学 网络中心,陕西 西安  710054)
  • 收稿日期:2010-08-30 出版日期:2011-06-20 发布日期:2011-07-14
  • 通讯作者: 焦继业
  • 作者简介:焦继业(1977-),男,西安电子科技大学博士研究生,E-mail: jiaojy@gamil.com.
  • 基金资助:

    陕西省自然科学基金资助项目(2009JM8004)

Co-processor implementation for fast face detection  in a system-on-chip

JIAO Jiye1;MU Rong2;HAO Yue1   

  1. (1. Ministry of Education Key Lab. of Wide Band-Gap Semiconductor Materials and Devices, Xidian Univ., Xi'an   710071, China|
    2. Network Center, Xi'an Univ. of Science and Technology, Xi'an   710054, China)
  • Received:2010-08-30 Online:2011-06-20 Published:2011-07-14
  • Contact: JIAO Jiye

摘要:

提出了一种改进的、适合硬件并行实现的Adaboost算法多层分类器协处理器架构.该协处理器由积分图数据快速读取模块、多层分类器Haar型特征值运算模块、DMA数据存取模块和协处理器接口模块组成,模块间采用流水线以及FIFO缓存实现数据并行处理,用于人脸检测SoC中加速人脸检测迭代过程.将该协处理器嵌入一个实际的人脸检测SoC中,只增加了SoC的少量面积,却明显提高了人脸检测的处理速度.人脸检测SoC在CYCLONE-Ⅱ EP2C70 FPGA上通过验证.实验结果显示,在系统工作频率为70MHz时,能以10帧每秒的处理速度检测彩色QVGA图像中的人脸.

关键词: 人脸检测, Adaboost算法, 多层分类器, 协处理器

Abstract:

An improved co-processor architecture suitable for hardware parallel implementation is proposed to perform the feature classification based on the Adaboost algorithm. The co-processor consists of image quick access module, module for calculating the Haar features, DMA data transfer module, and interface to the co-processor module. Modules use the pipeline and FIFO buffer to process data to accelerate the iterative process of face detection. The co-processor only increases a small area in face detection SoC, but significantly improves the speed of face detection. In addition, we implement the proposed SoC on a CYCLONE-Ⅱ EP2C70 FPGA to show that object detection can be achieved at 10 frames per second at the system operating frequency of 70MHz on color QVGA camera video.

Key words: face detection, Adaboost algorithm, features classifiers, co-processor

中图分类号: 

  • TP391
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