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3DPVT
2002
IEEE

Probabilistic 3D Data Fusion for Adaptive Resolution Surface Generation

13 years 8 months ago
Probabilistic 3D Data Fusion for Adaptive Resolution Surface Generation
In this paper we present an algorithm for adaptive resolution integration of 3D data collected from multiple distributed sensors. The input to the algorithm is a set of 3D surface points and associated sensor models. Using a probabilistic rule, a surface probability function is generated that represents the probability that a particular volume of space contains the surface. The surface probability function is represented using an octree data structure; regions of space with samples of large covariance are stored at a coarser level than regions of space containing samples with smaller covariance. The algorithm outputs an adaptive resolution surface generated by connecting points that lie on the ridge of surface probability with triangles scaled to match the local discretization of space given by the octree. To demonstrate the performance of our algorithm, we present results from 3D data generated by scanning lidar and structure from motion.
Andrew E. Johnson, Roberto Manduchi
Added 14 Jul 2010
Updated 14 Jul 2010
Type Conference
Year 2002
Where 3DPVT
Authors Andrew E. Johnson, Roberto Manduchi
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