Research on the Application of Image-based Gesture Recognition Technology in Classical Industries

Yang Wang

doi:10.62051/2mt36577

Authors

Yang Wang

DOI:

https://doi.org/10.62051/2mt36577

Keywords:

Gesture recognition; Image recognition; Visual perception; Deep learning.

Abstract

In today's era of rapid technological development, the innovation of human-computer interaction technology is profoundly changing the way people live and work. Among them, gesture recognition technology, as a promising means of interaction, has gradually become an unstoppable trend in various classic industries. At present, gesture recognition technology is mainly divided into two categories: sensor-based data capture and vision-based non-contact perception. The former relies on high-precision sensors that can accurately capture subtle changes in movement; The latter uses advanced cameras and image processing technology to enable natural and contactless interactions. With the continuous progress of microelectronics technology and the wide application of deep learning technology, these two technologies have gradually shown a good trend of complementarity and integration, laying a solid foundation for the wide application of gesture recognition technology in many fields such as smart home, medical care, and transportation. However, the systematic comparison and evaluation of the performance boundaries, application scenarios, and user experience of these technologies is still insufficient. Through the analysis of sensor-based and vision technology, combined with practical application cases, this paper discusses its application potential and challenges in classic industries, and proposes corresponding future development directions.

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