Implementation of FAST Corner Detection and Natural Feature Tracking Algorithms on an Augmented Reality Application for Introducing Global Warming

Abstract

Global warming is an increasingly alarming environmental issue, making early education essential. To enhance students' understanding of its causes, an educational application based on augmented reality (AR) technology was developed. This application employs FAST Corner Detection and Natural Feature Tracking algorithms to detect natural markers on real-world objects. Recognized markers trigger interactive 3D objects and audio narration explaining key global warming factors, such as the greenhouse effect, pollution, and deforestation. The testing process was conducted in two stages: alpha testing using the black-box method to validate functionality, and beta testing, which involved distributing questionnaires to teachers to measure the perceived effectiveness and satisfaction level with the application. The results indicate that the application functions correctly and, based on user feedback, shows significant potential as an engaging and interactive learning medium for introducing environmental issues to students.