This project involves methods of background modeling in video for the purpose of segmentation between foreground (e.g. people, moving cars etc.) and background (e.g. sidewalks or roads but also more challenging cases such as vegetation and dynamic bodies of water). In numerous computer vision applications in video, a separation between the background and the foreground, which contains interest regions for a human viewer, is often required in the initial stage of processing.
Until several years ago, comprehensive labeled databases for the purpose of evaluating and comparing the performance of background segmentation methods in many scenarios, were not available in the computer vision community. In 2012, the website changedetection.net was launched with an extensive database of this kind and since then, much progress was made in this field regarding both the number of new algorithms proposed and segmentation performance.