Robust and efficient event detection for the monitoring of automated processes

We present a new approach for the detection of events in image sequences. Our method relies on a number of logical sensors that can be defined over specific regions of interest in the viewed scene. These sensors measure time varying image properties that can be attributed to primitive events of interest. Thus, the logical sensors can be viewed as a means to transform image data to a set of symbols that can assist event detection and activities interpretation. On top of these elementary sensors, temporal and logical aggregation mechanisms are used to define hierarchies of progressively more complex sensors, able to detect events having more complex semantics. Finally, scenario verification mechanisms are employed to achieve process monitoring, by checking whether events occur according to a predetermined order. The proposed framework has been tested and validated in an application involving monitoring of automated processes. The obtained results demonstrate that the proposed approach, despite its simplicity, provides a promising framework for vision based event detection in the context of such applications.