Change Detection with a Mobile Robot Using Reference Region Extraction Based on Multi-View Stereo

This study proposes a method for change detection by extracting small image pairs from recorded video pairs in patrol inspections of oil plants using a mobile robot equipped with a camera. While change detection methods often perform well in controlled laboratory environments, their performance tends to degrade in plant environments. This is because, in plant environments, the regions of change caused by anomalies within the images are often small, and the environments are structurally complex. In this study, to address this issue, we adopt an approach that extracts small image pairs from the target and reference images for change detection. Additionally, we develop a method for extracting small image pairs that considers the consistency of three-dimensional coordinates based on multi-view stereo. As a result, the proposed method achieved high-precision change detection, demonstrating its potential for application in patrol inspections of oil plants using a mobile robot.