1. Fetch your data
Setting
In this setting, people move around and interact in a public space and we want to identify complex activities, such as people walking together, fighting or meeting. The aim is to support security procedures in a public space, by identifying problematic events, such as a fight.Data
The data on which we build our identification is a set of recognized elementary (short-term) behaviors, such as a person running, moving abruptly or a person standing still.
The data were provided from the benchmark CAVIAR dataset.
Example
For our scenario we gather data about two persons (George and Alex) for specific moments in time, indicated by numeric timestamps. For each timestamp we hold the current person action status and the position in the space. Below we describe the gathered data both in everyday language and in the corresponding formal representation.
2. Embed your knowledge
Description
In this step embed your knowledge rule in the system. That rules reflecting on the different actions.Example
For example we provide formal descriptions of what constitutes that two persons fighting, they are close or move abruptly.
3. Recognise events in realtime
4. Get value out of the data
The output of the process allows a quick glimpse over a huge amount of data gathered within the day, summarizing the main events and problems that help you make decisions.
Now, you can provide this analysis as a service to others, or use the findings within your organization to do things, such as optimizing procedures, improving customer experience or minimizing risks.
