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註釋Abstract: "We compare two well known methods of computing with uncertain quantities as used for geometric reasoning in robotics and computer vision. One method represents errors with intervals and manipulates them using techniques from interval arithmetic and network relaxation. The other method uses normal probability distributions for representation and manipulates them with techniques from statistical estimation theory. We find that the method based on probabilities is better in terms of both speed and accuracy."