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Visual perception-based human-computer interaction information classification method for intelligent products

Author

Listed:
  • Liting Zhou
  • Xuan Li
  • Minmin Guo

Abstract

This paper proposes a new intelligent product human-computer interaction information classification method based on visual perception. Design smart product human-computer interaction information collection device to realise rapid and accurate collection of smart product human-computer interaction information, and fusion processing of the collected information. The ISA model is built according to the principle of visual perception, and the model is optimised by the gradient descent method. The optimised model is used to extract the information attribute characteristics, and the intelligent product human-computer interaction information classification is carried out according to the information attribute characteristics. The experimental results show that the accuracy of information classification of this method is always above 94.7%, and the average classification time is 0.53 s, which verifies the superiority of the method.

Suggested Citation

  • Liting Zhou & Xuan Li & Minmin Guo, 2023. "Visual perception-based human-computer interaction information classification method for intelligent products," International Journal of Product Development, Inderscience Enterprises Ltd, vol. 27(1/2), pages 28-40.
    • Handle: RePEc:ids:ijpdev:v:27:y:2023:i:1/2:p:28-40
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