Interactive visual computer vision analysis based on artificial intelligence technology in intelligent education

Yan Hu, Qiang Qiang Li, Shih wei Hsu

Research output: Journal PublicationArticlepeer-review

2 Citations (Scopus)

Abstract

In order to improve the effect of intelligent education and teaching, under the guidance of artificial intelligence technology, this article combines interactive visual computer vision analysis algorithms to construct an intelligent education assistance system based on machine vision. In the case of multiple points within the movement point area, the calculation is performed by offsetting from the center of the point area. Visual self-calibration reflects the mapping relationship between the image coordinate system and the camera coordinate system by automatically obtaining the relationship between the vectors by moving to different positions. Aiming at the problem of slow template matching, this paper uses fast normalized correlation, integral image and fast Fourier transform methods to optimize the template recognition speed, and uses surface fitting methods to locate the matching results in sub-pixels. Finally, this article combines experiments to verify the performance of the intelligent education system constructed in this article. The research results show that the algorithm model constructed in this paper has certain practical effects.

Original languageEnglish
JournalNeural Computing and Applications
Early online date20 Jul 2021
DOIs
Publication statusPublished Online - 20 Jul 2021

Keywords

  • Artificial intelligence
  • Intelligent education
  • Interactive
  • Machine vision
  • Visualization

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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