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

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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.

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Acknowledgements

This work was supported by Project of Henan Soft Science Research Plan (212400410487)), “Industry-university-research-investment-service-application” New mode drives the transformation of scientific and technological achievements in Colleges and universities of Henan Province.

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Authors and Affiliations

  1. Department of Information Engineering, The Open University of HeNan, Zhengzhou, 450000, China

    Yan Hu

  2. Department of Mechanical and Electrical Engineering, The Open University of HeNan, Zhengzhou, 450000, China

    QiangQiang Li

  3. University of Nottingham Ningbo China, Ningbo, 315100, China

    Shih-wei Hsu

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  1. Yan Hu
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  2. QiangQiang Li
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  3. Shih-wei Hsu
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Correspondence to Shih-wei Hsu.

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Hu, Y., Li, Q. & Hsu, Sw. Interactive visual computer vision analysis based on artificial intelligence technology in intelligent education. Neural Comput & Applic 34, 9315–9333 (2022). https://doi.org/10.1007/s00521-021-06285-z

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