Image time series mining for dynamic scene understanding
Patrick Héas, Mihai P. Datcu, M. Abdellani, Alain Giros, Philippe Marthon · 2004
In this paper, a dynamic scene understanding concept is proposed and applied on multispectral image time series. Information mining enables the explorations and discovery of spatio temporal patterns localized in given spatio temporal windows. With this in mind, a hierarchical information representation is developed. It comprises different levels in which the data is modeled so that the relevant information is transmitted through the architecture, according to a query and to several assumptions made on the models employed. There are mainly four components: feature extraction, reduction of dimensionality, clustering and interactive exploration.