Abstract
We present a robust and fast method for on-line creation of local maps based on stereo vision for vehicles operating in off-road environments. A 3D vision sensor system with a high accuracy even at long ranges and wide field of view is used as the only sensor input. Due to the hierarchical mode of operation, dense stereo matching on image resolution 1200 ×525 and a disparity range of 280 becomes feasible at 10 fps. Beside of an achieved speedup factor of 6.47, a significant increase in the density of resulting disparity maps on real-world scenes has been achieved. Multiple captured views are aligned and integrated into a probabilistic elevation map suited for modeling dynamic environments. Efficient computations in the u-disparity-space and a stereo sensor model are at the core of the iterative update process.
The project has been funded by the Austrian Security Research Program KIRAS - an initiative of the Austrian Federal Ministry for Transport, Innovation and Technology (bmvit).
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Kadiofsky, T., Weichselbaum, J., Zinner, C. (2012). Off-road Terrain Mapping Based on Dense Hierarchical Real-Time Stereo Vision. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2012. Lecture Notes in Computer Science, vol 7431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33179-4_39
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DOI: https://doi.org/10.1007/978-3-642-33179-4_39
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