Journal of System Simulation
Abstract
Abstract: A precise attention tracking system based on machine vision is designed to address the difficulty in studying students' attention allocation. The system includes an image capture device and an accurate attention tracking algorithm. The image capture device can capture the clearer ocular images. The pupil center localization algorithm replaces VGG16 with lightweight MobileNetv3 and uses twostage feature fusion and center keypoint prediction techniques to improve the speed and accuracy. The algorithm achieves a speed of up to 36 frames/s and 97.42% accuracy. The gaze tracking algorithm compensates for the head movements to achieve the meticulous gaze tracking. An interactive software for assessing cognitive abilities in school-age children is developed. The software calculates the eye movement indicators by using the collected gaze coordinates and evaluates the cognitive abilities based on psychological theory, and provides a reference for the psychology and education research.
Recommended Citation
Liu, Jiyuan; Qi, Hanwen; Liu, Zhicheng; Fei, Minrui; and Zhang, Kun
(2023)
"A Precise Attention Tracking System Based on Computer Vision,"
Journal of System Simulation: Vol. 35:
Iss.
10, Article 2.
DOI: 10.16182/j.issn1004731x.joss.23-FZ0829
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol35/iss10/2
First Page
2087
Last Page
2100
CLC
TP391.7
Recommended Citation
Liu Jiyuan, Qi Hanwen, Liu Zhicheng, et al. A Precise Attention Tracking System Based on Computer Vision[J]. Journal of System Simulation, 2023, 35(10): 2087-2100.
DOI
10.16182/j.issn1004731x.joss.23-FZ0829
Included in
Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Science Commons