Zahraa Tarek¹, Samaa M. Shohieb^1,*, Abdelghafar M. Elhady², El-Sayed M. El-kenawy³, Mahmoud Y. Shams⁴

Computer Systems Science and Engineering, Vol.45, No.3, pp. 3195-3213, 2023, DOI:10.32604/csse.2023.034092

Abstract The ability to detect and localize the human eye is critical for use in security applications and human identification and verification systems. This is because eye recognition algorithms have multiple challenges, such as multi-pose variations, ocular parts, and illumination. Moreover, the modern security applications fail to detect facial expressions from eye images. In this paper, a Speeded-Up Roust Feature (SURF) Algorithm was utilized to localize the face images of the enrolled subjects. We highlighted on eye and pupil parts to be detected based on SURF, Hough Circle Transform (HCT), and Local Binary Pattern (LBP). Afterward, Deep Belief Neural Networks (DBNN)… More >

Pingping Yu¹, Wenjie Duan¹, Yi Sun², Ning Cao^{3, *}, Zhenzhou Wang¹, Guojun Lu⁴

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1199-1217, 2020, DOI:10.32604/cmc.2020.010384

Abstract Human eye detection has become an area of interest in the field of computer vision with an extensive range of applications in human-computer interaction, disease diagnosis, and psychological and physiological studies. Gaze-tracking systems are an important research topic in the human-computer interaction field. As one of the core modules of the head-mounted gaze-tracking system, pupil positioning affects the accuracy and stability of the system. By tracking eye movements to better locate the center of the pupil, this paper proposes a method for pupil positioning based on the starburst model. The method uses vertical and horizontal coordinate integral projections in the… More >