This work deals with the automatic detection of complex situations in image sequences within the context of video surveillance. When handling data from natural environments, challenges arise. This study expands the utilized formalism to address issues of blurriness, missing information, and complexity, demonstrates the robustness of situation detection in natural scenarios, and highlights its generic applicability beyond the boundaries of discourse domains.