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30 April 2009 Tessellated structure from motion for midrange perception and tactical planning
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Abstract
A typical structure from motion (SFM) technique is to construct 3-D structures from the observation of the motions of salient features tracked over time. Although the sparse feature-based SFM provides additional solutions to robotic platforms as a tool to augment navigation performance, the technique often fails to produce dense 3-D structures due to the sparseness that is introduced during the feature selection and matching processes. For midrange sensing and tactical planning, it is important to have a dense map that is able to provide not only 3-D coordinates of features, but also clustered terrain information around the features for better thematic representation of the scene. In order to overcome the shortfalls embedded in the sparse feature-based SFM, we propose an approach that uses Voronoi decomposition with an equidistance-based triangulation that is applied to each of segmented and classified regions. The set of the circumcenters of the circum-hyperspheres used in the triangulation is formed with the feature points extracted from the SFM processing. We also apply flat surface detection to find traversable surface for a robotic vehicle to be able to maneuver safely on.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Minbo Shim and Samson Yilma "Tessellated structure from motion for midrange perception and tactical planning", Proc. SPIE 7332, Unmanned Systems Technology XI, 733214 (30 April 2009); https://doi.org/10.1117/12.818959
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