Current research in service robotics is more and more aimed at applications in real home environments. In such context, the ability to track and understand human movements is very important for a robot, for human-robot-interaction as well as other purposes, e.g. proactive behavior, gestures and motions are an important channel of information about the humans intentions. Before actual motion tracking can take place, it is necessary to initialize the tracking system with a hypothesis about the position and pose of the person who shall be tracked. For collaboration with humans in an unknown environment, the system should perform this step automatically. Therefore, we propose an approach to initialize a usable model of a human standing in front of the system by determining the position and height of a human from its silhouette with a cascade of simple metrics, e.g. compactness and position of the neck.