Abstract
The large variety of influencing factors requires the manual creation and optimization of person trackers for different environments as well as different views, such as in a distributed network of cameras. The manual creation and adjustments are time-consuming as well as prone to error and therefore expensive. We propose a system that uses basic computer-vision building blocks to automatically create and optimize a person tracker, using only a few annotated camera frames. An evaluation shows that our system creates target-oriented trackers from largely very basic methods, that can compare to manually, published person trackers. The system has the potential to drastically reduce the cost of creating person trackers for new environments and optimizing it for every single camera in a camera network.