Image Understanding for Alpine Environmental Monitoring

In an era of anthropogenic global change, there is an increasing need to measure and monitor our natural environment. Time-lapse photography can provide compelling visualisations of how natural systems behave over time, for example, glacial recession due to global warming. However, in addition to visualisation, cameras can also be used as sensors, making measurements that aid the scientific understanding of natural systems. The aim of this project is to develop novel computer vision techniques to monitor long-term change in outdoor environments, turning an SLR into a useful sensor for environmental monitoring. In particular we will use time-lapse imagery to extract detailed surface information and subtle motion in scenes, something that is not possible using existing satellite-based techniques. Reaching this goal will require improved techniques for robust image understanding that are capable of extracting useful information, such as very small scene motion, over long timescales and with wildly varying appearance and illumination conditions.