In this paper, we describe a method for estimating external camera parameters in real time. We investigated the effectiveness of this method for annotating real scenes with 3-D virtual objects on a wearable computer. The proposed method enables determining known natural feature points of objects through multiplied color histogram matching and template matching. This external-camera-parameter calculation method consists of three algorithms for PnP problems, and it uses each algorithm selectively. We implemented an experimental system based on our method on a wearable vision system. This experimental system can annotate real objects with 3D virtual objects by using the proposed method. The system was implemented in order to enable effective annotation in a mixed-reality environment on a wearable computing system. The system consists of an ultra small CCD camera set at the user's eye, an ultra small display, and a computer. This computer uses the proposed method to determine the camera parameters. It then renders virtual objects based on the camera parameters and synthesizes images on a display. The system works at 10 frames per second.