Estimating camera position and posture can be applied to the fields of augmented reality and robot navigation. In these fields, to obtain absolute position and posture of the camera, sensor-based methods using GPS and magentic sensors and vision-based methods using input images from the camera have been investigated. How- ever, sensor-based methods are difficult to synchronize the camera and sensors accurately, and usable environments are limited according to selection of sensors. On the other hand, vision-based methods needs to allocate many artificial markers otherwise an estimation error will accumulate. Thus, it is difficult to use such methods in large and natural environments. This paper proposes a vision-based camera position and posture estimation method for large environments, which does not require sensors and artificial markers by detecting natural feature points from