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Locating all obstacles around a moving robot and classifying them as stable obstacles or not by a sensor such as an omnidirectional camera are essential for the robot's smooth movement and avoiding problems in calibrating many cameras. However, there are few works on locating and classifying all obstacles around a robot while it is moving by only one omnidirectional camera. In order to locate obstacles, we regard floor boundary points where robots can measure the distance from the robot by one omnidirectional camera as obstacles. Tracking them, we can classify obstacles by comparing the movement of each tracked point with odometry data. Moreover, our method changes a threshold to detect the points based on the result of comparing in order to enhance classification. The classification ratio of our method is 85.0%, which is four times higher than that of a method without changing a parameter to detect the points.