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Implementation System of Human Eye Tracking Algorithm Based on FPGA

机译：基于FPGA的人眼跟踪算法实现系统

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With the high-speed development of transportation industry, highway traffic safety has become a considerable problem. Meanwhile, with the development of embedded system and hardware chip, in recent years, human eye detection eye tracking and positioning technology have been more and more widely used in man-machine interaction, security access control and visual detection.In this paper, the high parallelism of FPGA was utilized to realize an elliptical approximate real-time human eye tracking system, which was achieved by the series register structure and random sample consensus (RANSAC), thus improving the speed of image processing without using external memory. Because eye images acquired by the camera often generate a lot of noises due to uneven light and dark background, the preprocessing technologies such as color conversion, image filtering, histogram modification and image sharpening were adopted. In terms of feature extraction of images, the eye tracking algorithm in this paper adopted seven-section rectangular eye tracking characteristic method, which increased a section between the mouth and the nose on the basis of the traditional six-section method, so its recognition accuracy is much higher. It is convenient for the realization of hardware parallel system in FPGA. Finally, aiming at the accuracy and real-time performance of the design system, a more comprehensive simulation test was carried out.The human eye tracking system was verified on DE2-115 multimedia development platform, and the performance of VGA (resolution: 640 x 480) images of 8-bit grayscale was tested. The results showed that the detection speed of this system was about 47 frames per second under the condition that the detection rate of human face (front face, no inclination) was 93%, which reached the real-time detection level. Additionally, the accuracy of eye tracking based on FPGA system was more than 95%, and it has achieved ideal results in real-time performance and robustness.
机译：随着运输业的高速发展，公路交通安全已成为一个相当大的问题。同时，随着嵌入式系统和硬件芯片的发展，近年来，人眼检测中的人眼跟踪和定位技术已越来越广泛地应用于人机交互，安全访问控制和视觉检测中。利用FPGA的并行性，通过串行寄存器结构和随机样本一致性（RANSAC）实现了椭圆近似实时人眼跟踪系统，从而在不使用外部存储器的情况下提高了图像处理速度。由于摄像机采集到的人眼图像经常因光线不均匀和背景暗而产生大量噪声，因此采用了诸如色彩转换，图像过滤，直方图修改和图像锐化的预处理技术。在图像特征提取方面，本文的眼睛跟踪算法采用了七段式矩形眼睛跟踪特征方法，在传统的六段式方法的基础上增加了嘴与鼻子之间的区域，从而提高了识别精度。更高。便于在FPGA中实现硬件并行系统。最后，针对设计系统的准确性和实时性，进行了更全面的仿真测试，在DE2-115多媒体开发平台上对人眼跟踪系统进行了验证，并验证了VGA的性能（分辨率：640 x 480）测试了8位灰度图像。结果表明，该系统在人脸（正面，无倾斜）的检测率为93％的条件下，检测速度约为每秒47帧，达到了实时检测水平。此外，基于FPGA系统的眼动追踪的准确性超过95％，并且在实时性能和鲁棒性方面取得了理想的结果。

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