Zippered polygon meshes from range images
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
A signal processing approach to fair surface design
SIGGRAPH '95 Proceedings of the 22nd 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
A fast surface-based procedure for object reconstruction from 3D scattered points
Computer Vision and Image Understanding
Geometric fusion for a hand-held 3D sensor
Machine Vision and Applications
Real-time 3D model acquisition
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Multi-View 3D Model Reconstruction: Exploitation of Color Homogeneity in Voxel Mask
ICIG '04 Proceedings of the Third International Conference on Image and Graphics
Automatic 3D modeling of textured cultural heritage objects
IEEE Transactions on Image Processing
Accurate integration of multi-view range images using k-means clustering
Pattern Recognition
A clustering approach to free form surface reconstruction from multi-view range images
Image and Vision Computing
An autonomous six-DOF eye-in-hand system for in situ 3D object modeling
International Journal of Robotics Research
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Existing integration algorithms often assume that the registration error of neighbouring views is an order of magnitude less than the measurement error [3]. This assumption is very restrictive that automatic registration algorithms can hardly meet. In this paper, we develop a novel integration algorithm, robust to both large registration errors and heavy scanning noise. Firstly, a pre-processing procedure is developed to automatically triangulate a single range image and remove noisy triangles. Secondly, we shift points along their orientations by the projection of their resulting correspondence vectors so that new correspondences can approach together, leading large registration errors to be compensated. Thirdly, overlapping areas between neighbouring views are detected and integrated, considering the confidence of triangles, which is a function of the including angle between the centroid point vector of a triangle and its normal vector. The outcome of integration is a set of disconnected triangles where gaps are caused by the removal of overlapping triangles with low confidence. Fourthly, the disconnected triangles are connected based on the principle of maximizing interior angles. Since the created triangular mesh is not necessarily smooth, finally, we minimize the weighted orientation variation. The experimental results based on real images show that the proposed algorithm significantly outperforms an existing algorithm and is robust to both registration error and scanning noise.