A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Surface reconstruction from unorganized points
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
A General Surface Approach to the Integration of a Set of Range Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
A volumetric method for building complex models from range images
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
An efficient volumetric method for building closed triangular meshes from 3-D image and point data
Proceedings of the conference on Graphics interface '97
Geometric fusion for a hand-held 3D sensor
Machine Vision and Applications
Reading between the Lines: A Method for Extracting Dynamic 3D with Texture
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Skeleton-based surface construction from unorganized curves
CGIM '08 Proceedings of the Tenth IASTED International Conference on Computer Graphics and Imaging
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Traditional approaches for surface reconstruction from range data require that the input data be either range images or unorganized sets of points. Since a large number of range sensors provide data along curvilinear patterns such as profiles, this paper presents an approach for reconstructing a surface from a set of unorganized curves. A strategy for updating the reconstructed surface during data acquisition is described as well. Curves are accumulated in a volumetric structure in which a vector field is built and updated. The information that is needed for efficient curve registration is also directly available in this vector field. This leads to a unified modeling approach combining surface reconstruction and curve registration. The algorithm implementing the approach is of linear complexity with respect to the number of input curves and makes it suitable for interactive modeling. Simulated data based on a set of six curvilinear patterns as well as data acquired with a range sensor are used to illustrate the various steps of the algorithm.