Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Surface reconstruction from unorganized points
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Zippered polygon meshes from range images
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
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 Algorithm for Finding Best Matches in Logarithmic Expected Time
ACM Transactions on Mathematical Software (TOMS)
Reliable Surface Reconstructiuon from Multiple Range Images
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
A New Multiscale Representation for Shapes and Its Application to Blood Vessel Recovery
SIAM Journal on Scientific Computing
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In this paper, we present a robust method for creating a triangulated surface mesh from multiple range images. Our method merges a set of range images into a volumetric implicit-surface representation which is converted to a surface mesh using a variant of the marching-cubes algorithm. Unlike previous techniques based on implicit-surface representations our method estimates the signed distance to the object surface by finding a [consensus of locally coheren observations of the surface. We call this method the consensus-surface algorithm]. This algorithm effectively eliminates many of the troublesome effects of noise and extraneous surface observations without sacrificing the accuracy of the resulting surface. We utilize octrees to represent volumetric implicit surfaces---effectively reducing the computation and memory requirements of the volumetric representation without sacrificing accuracy of the resulting surface. We present results which demonstrate that our consensus-surface algorithm can construct accurate geometric models from rather noisy input range data.