Revisiting Change Detection Methods for their Application to Serac Fall Time-Lapse Monitoring 文章

ArXiv CS.CV2026-05-28NEWSen作者: Arthur D\'er\'edel, Carlos Crispim-Junior, Pierre Lemaire, Johan Berthet, Laure Tougne Rodet

摘要

arXiv:2605.28100v1 Announce Type: new Abstract: In an era where climate change aggravates environmental uncertainties, the identification and detection of event precursors are becoming crucial to mitigate the impacts of disastrous natural hazards. While classical sensors such as interferometric lasers or seismometers are reliable, their widespread deployment is often hindered by logistical and economic barriers, leaving numerous blind spots. Time-lapse cameras, which already provide cost-effective, high-resolution visual context to such sensors, present a promising alternative. However, processing their output automatically faces significant challenges, notably linked to extreme shape and lighting variations. Overcoming those issues is essential to deploy them at large-scale as a monitoring tool. This paper introduces a novel sub-task of change detection, namely volumetric change detection, applied to time-lapse cameras and slope instabilities.