Face detection system design for real time high resolution smart camera

Yasir Mohd-Mustafah, A. Bigdeli, A. Azman, B. Lovell
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引用次数: 26

Abstract

Recognizing faces in a crowd in real-time is a key feature which would significantly enhance Intelligent Surveillance Systems. Using a smart camera as a tool to extract faces for recognition would greatly reduce the computational load on the main processing unit. Main processing unit would not be overloaded by the demands of the high data rates of the video and could be designed solely for face recognition. The challenge is with the increasing speed and resolution of the camera sensors, a fast and robust face detection system is required for real time operation. In this paper we report on a multiple-stage face detection system that is designed for implementation on an FPGA based high resolution smart camera system. The system consist of filter stages to greatly reduce the region of interest in video image, followed by a face detection stage to accurately locate the faces. For filter stage, the algorithm is designed to be very fast so that it can be processed in real time. Meanwhile, for face detection stage, a hardware and software co-design technique is utilised to accelerate it.
人脸检测系统设计为实时高分辨率智能摄像头
实时识别人群中的人脸是提高智能监控系统性能的关键。使用智能相机作为提取人脸进行识别的工具,将大大减少主处理单元的计算负荷。主处理单元不会因视频高数据速率的需求而过载,可以单独设计用于人脸识别。随着相机传感器速度和分辨率的不断提高,需要一个快速、鲁棒的人脸检测系统来实现实时操作。在本文中,我们报告了一个多级人脸检测系统,该系统设计用于实现基于FPGA的高分辨率智能相机系统。该系统由滤波阶段和人脸检测阶段组成,滤波阶段可以大大减小视频图像中的感兴趣区域,人脸检测阶段可以精确定位人脸。在滤波阶段,算法设计得非常快,可以实时处理。同时,在人脸检测阶段,采用了软硬件协同设计技术来加快人脸检测速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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