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.
Liu, Jiyuan; Qi, Hanwen; Liu, Zhicheng; Fei, Minrui; and Zhang, Kun
"A Precise Attention Tracking System Based on Computer Vision,"
Journal of System Simulation: Vol. 35:
10, Article 2.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol35/iss10/2
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.
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