23 June 2000 Combining computer graphics and computer vision for probabilistic visual robot navigation
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Abstract
In this contribution we present how techniques from computer graphics and computer vision can be combined to finally navigate a robot in natural environment based on visual information. The key idea is to reconstruct an image based scene model, which is used in the navigation task to judge position hypotheses by comparing the taken camera image with a virtual image created from the image based scene model. Computer graphics contributes to a method for photo-realistic rendering in real- time, computer vision methods are applied to fully automatically reconstruct the scene model from image sequences taken by a hand-held camera or a moving platform. During navigation, a probabilistic state estimation algorithm is applied to handle uncertainty in the image acquisition process and the dynamic model of the moving platform. We present experiments which proof that our proposed approach, i.e. using an image based scene model for navigation, is capable to globally localize a moving platform with reasonable effort. Using off-the-shelf computer graphics hardware even real-time navigation is possible.
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Benno Heigl, Joachim Denzler, Heinrich Niemann, "Combining computer graphics and computer vision for probabilistic visual robot navigation", Proc. SPIE 4023, Enhanced and Synthetic Vision 2000, (23 June 2000); doi: 10.1117/12.389345; https://doi.org/10.1117/12.389345
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