Factor graph methods for three-dimensional shape reconstruction as applied to LIDAR imaging
JOSA A, Vol. 21, Issue 10, pp. 1855-1868 (2004)
http://dx.doi.org/10.1364/JOSAA.21.001855
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Abstract
Two methods based on factor graphs for reconstructing the three-dimensional (3D) shape of an object from a series of two-dimensional images are presented. First, a factor graph model is developed for image segmentation to obtain silhouettes from raw images; the shape-from-silhouette technique is then applied to yield the 3D reconstruction of the object. The second method presented is a direct 3D reconstruction of the object using a factor graph model for the voxels of the reconstruction. While both methods should be applicable to a variety of input data types, they will be developed and demonstrated for a particular application involving the LIDAR imaging of a submerged target. Results from simulations and from real LIDAR data are shown that detail the performance of the methods.
© 2004 Optical Society of America
OCIS Codes
(100.2000) Image processing : Digital image processing
(100.3010) Image processing : Image reconstruction techniques
(100.6890) Image processing : Three-dimensional image processing
Citation
Robert J. Drost and Andrew C. Singer, "Factor graph methods for three-dimensional shape reconstruction as applied to LIDAR imaging," J. Opt. Soc. Am. A 21, 1855-1868 (2004)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-21-10-1855
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