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A Robust Method for Computing Vehicle Ego-motion
In IEEE Intelligent Vehicles Symposium (IV2000, (2000)
Аннотация
We describe a robust method for computing the ego-motion of the vehicle relative to the road using input from a single camera mounted next to the rear view mirror. Since feature points are unreliable in cluttered scenes we use direct methods where image values in the two images are combined in a global probability function. Combined with the use of probability distribution matrices, this enables the formulation of a robust method that can ignore large number of outliers as one would encounter in real traffic situations. The method has been tested in real world environments and has been shown to be robust to glare, rain and moving objects in the scene. 1 Introduction Accurate estimation of the ego-motion of the vehicle relative to the road is a key component for autonomous driving and computer vision based driving assistance. We describe a robust method for computing the ego-motion of the vehicle relative to the road using input from a single camera rigidly mounted next to the rear vi...
