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Real-time camera tracking is steadily gaining in importance due to the drive from various applications, such as AR(augmented reality), human-machine interface, and ubiquitous computing. However, a real-time camera tracking using a single camera in an unknown environment is not a trivial work. In this paper, we describe a real-time camera tracking framework specifically designed to track a monocular camera in a desktop workspace. Basic idea of the proposed scheme is that a particle filter-based camera tracking is linked to multiple feature trackers for the feature mapping via measurement covariances. Moreover, we split the camera tracking and feature mapping into two separate tasks, and they are handled in two parallel processes. We demonstrate the effectiveness of the proposed approach within a desktop environment in real-time. It can be applicable to an augmented reality-based gaming system.