Range Image Fusion for Object Reconstruction and Modeling

  • Authors:
  • Affiliations:
  • Venue:
  • CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
  • Year:
  • 2004

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Abstract

A complete pipeline of data fusion from rangeimages for a 3D object reconstruction and modeling ispresented. The proposed approach includes multi-viewregistration, data integration, smoothing, andresampling. Firstly, the range images taken frommultiple views are registered through a set oftranslation and rotation matrices whose coefficientsare carefully pre-calculated. Then, a definition andtwo criteria to overlap elimination are provided as thefoundation together with kd-tree data structure andnearest neighbor searching technique for dataintegration. A surface-based smoothing filter and areliable resampling method, called the ball-travel-basedresampling, are also given for surface qualityimprovement and data size reduction. All theoperations manipulate range images directly withoutadditional preprocessing operation, such as meshingor implicit surface function calculation to each rangeimage, and thus provide a straightforward way to fuseany 3D data. The approach is applied to various rangedata sets of objects with different geometry shapes. Theexperimental results demonstrate the efficiency andapplicability of the proposed method.