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The first comparison of different types of cameras (as opposed to different algorithms) for the ego-motion estimation problem is presented. As technology and computational power increase, the effectiveness of visual algorithms is limited only by inherent statistical uncertainties in the problems they are solving. The Fisher information matrix is a powerful analysis technique that can apply to any problem that involves searching for a parameter set that minimizes an error function. This includes problems such as pose-estimation, object recognition, or classification. Designing camera systems optimized for particular tasks may significantly improve the success of visual algorithms.