Automatic Museum Audio Guide

• Main Authors: Noelia Vallez, Stephan Krauss, Jose Luis Espinosa-Aranda, Alain Pagani, Kasra Seirafi, Oscar Deniz
• Format: Article
• Language: English
• Published: MDPI AG 2020-01-01
• Series: Sensors
• Subjects: internet of things (iot); computer vision; automatic audioguide; artificial intelligence; systems on chip (soc)
• Online Access: https://www.mdpi.com/1424-8220/20/3/779

An automatic “museum audio guide” is presented as a new type of audio guide for museums. The device consists of a headset equipped with a camera that captures exhibit pictures and the eyes of things computer vision device (EoT). The EoT board is capable of recognizing artworks using features from accelerated segment test (FAST) keypoints and a random forest classifier, and is able to be used for an entire day without the need to recharge the batteries. In addition, an application logic has been implemented, which allows for a special highly-efficient behavior upon recognition of the painting. Two different use case scenarios have been implemented. The main testing was performed with a piloting phase in a real world museum. Results show that the system keeps its promises regarding its main benefit, which is simplicity of use and the user’s preference of the proposed system over traditional audioguides.