Research on the Application of Intelligent Assistive Technology in Tourism Public Service for Special Population

Abstract

There are a large number of disabled people in China, but there are few facilities specially designed to provide convenience for special people in tourism public auxiliary services. How to strengthen humanized design and let special people enjoy special tourism public auxiliary services is a topic worth studying in the current construction of public facilities in China. To solve this problem, this paper designs and builds a sign language recognition system for hearing impaired people based on artificial intelligence deep learning technology. In this paper, a 3D convolution neural network sign language recognition method based on multi-modal homologous data is proposed. By constructing a dual-row depth neural network, the distinguishing spatio-temporal features of dynamic sign language are extracted and learned from infrared images and contour images layer by layer, and finally the two independent data classification results are fused by fusion strategy. The sign language recognition system designed and built in this paper has been verified in practical application, which can recognize and display the sign language in the camera in real time, and has strong practicability.