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This paper addresses the problem of finding people in domestic environments utilizing a mobile robot. Companion robots, which should provide different services, must be able to robustly estimate the user's position. While detecting people in an upright pose is mainly solved, most of the users' various poses in living environments are hard to detect. We present a tracking framework that incorporates state-of-the-art detection modules, but also a novel approach for visually detecting the presence of people resting at previously known seating places in arbitrary poses. The method is based on a contextual color model of the respective place in the environment and a color model of the user's appearance. The system has been tested by evaluating the robot's capability to find the user in a 3-room apartment in a hide and seek scenario.