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Dr Laura Leal-Taixé is a Sofja Kovalevskaja Award Winner who heads a research group at the Chair for Computer Vision and Artificial Intelligence at the Technical University of Munich (TUM).
This is the kind of social information the computer scientist, who recently moved to Munich from Barcelona, wants to integrate into digital maps in her “Social Maps” project. So far, these services do not factor in how and when people interact in public spaces and the movement patterns that result – they neglect human traffic flows of pedestrians, cyclists or even schoolchildren. “What is usually a clear path can quite suddenly become completely blocked because a group of tourists crops up or lots of children all rush out of school onto the street at the same time where their parents are waiting in their cars to pick them up,” says Leal-Taixé.
She wants to capture and evaluate dynamic scenes like this in video sequences using special mathematical tools. These algorithms are not only able to analyse human traffic flows, they can even predict them. This could also be useful for town planners. When building a railway station, for example, it would make it easier to plan where and how many exits are required to channel commuters. Even if it does take a while before digital maps tell you the best time to head for the Octoberfest – the “new Municher” has already bought her dirndl.