Many tabletop systems have been developed to facilitate face-to-face collaboration and work at small meetings. These systems often require users to attach sensors to their bodies to identify their positions, but attaching a sensor to one’s body can be bothersome and annoying, and user position and posture may be restricted depending on where the sensor is attached. We have proposed a technique for estimating user position in a tabletop system by image recognition and implemented a tabletop system having a user position identification function incorporating the proposed technique. This technique first obtains touch points and hand-area information from touch operations performed by the user, and establishes an association between the touch points and hand from those positional relationships. Since the direction in which a hand is extended can be derived from that hand’s touch information, the position of the user of the touch points belonging to that hand can be estimated. As part of this study, we also implemented a photo-object manipulation application, which has a function for orienting a photo object to face the user based on the results of the above user-position estimation technique. We performed an experiment to evaluate the position identification rate, and found that the proposed technique could identify user position with high accuracy.