Open Access

RETRACTION

RETRACTED: Implementation System of Human Eye Tracking Algorithm Based on FPGA

Zhong Liu^1,2, Xin’an Wang¹, Chengjun Sun¹, Ken Lu³

1 Peking University, Shenzhen Graduate Schools, Shenzhen, 518000, China.
2 School of Electronics Engineering and Computer Science, Peking Universitye, Beijing, 100871, China.
3 iFutureLab Inc.955 Alma St., Suite B, Palo Alto, CA 94301, USA.

* Corresponding Author: Xin’an Wang. Email: .

Computers, Materials & Continua 2019, 58(3), 653-664. https://doi.org/10.32604/cmc.2019.04597

Abstract

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: 640×480) 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.

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Citations