Design of signage guidance system for tourist attractions based on computer vision technology

Abstract

In order to improve tourists’ sense of touring experience, this research proposes a signage navigation system for mobile scenic spots. Firstly, the system uses a recurrent neural network algorithm incorporating convolutional neural network for image recognition function to obtain relevant information through image recognition. Then the target localization of the image is performed according to the single-stage target detection algorithm, and the location of the landscape in which the user is located is localized by the recognized image information. The results show that the algorithm can achieve 86.7% recognition accuracy, and it can recognize part of the image samples when the recognition time reaches the range of 0.8 min–1 min. The single-stage target detection algorithm has a localization accuracy of 97.2% with a minimum loss rate of 1.1%. And the algorithm has high average accuracy and full class average accuracy values. The system has good application value.