High-Performance Real-Time Face-Detection Architecture for HCI Applications

Dongil Han, Jongho Choi
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引用次数: 3

Abstract

This paper proposes a novel hardware structure and FPGA implementation method for real-time detection of multiple human faces with robustness against illumination variations and Rotated faces. These are designed to greatly improve face detection in various environments, using the Adaboost learning algorithm and MCT techniques, Rotation Transformation, which is robust against variable illumination and rotated faces. The overall structure of proposed hardware is composed of a Color Space Converter, Noise Filter, Memory Controller Interface, Rotation Transformation, MCT (Modified Census Transform), Candidate Detector/Confidence Mapper, Position Resizer, Data Grouper, Overlay Processor and Color Overlay Processor. The experiment was conducted in various environments using a QVGA Camera, LCD Display and Virtext5 XC5VLX330 FF1760 FPGA, made by Xilinx. Implementation and verification results showed that it is possible to detect at least 32 faces in a wide variety of sizes at a maximum speed of 149 frames per second in real time.
HCI应用的高性能实时人脸检测架构
本文提出了一种新的硬件结构和FPGA实现方法,用于实时检测多人脸,具有对光照变化和旋转人脸的鲁棒性。使用Adaboost学习算法和MCT技术,旋转变换,这对可变光照和旋转的面部具有鲁棒性,这些设计大大提高了在各种环境下的面部检测。提出的硬件整体结构由颜色空间转换器、噪声滤波器、内存控制器接口、旋转变换、修正普查变换、候选检测器/置信度映射器、位置调整器、数据分组器、覆盖处理器和颜色覆盖处理器组成。实验采用Xilinx公司的QVGA摄像头、LCD显示屏和Virtext5 XC5VLX330 FF1760 FPGA在各种环境下进行。实现和验证结果表明,它可以以每秒149帧的最大速度实时检测至少32张不同大小的人脸。
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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