Multi-view 3D scanned data registration
Pages 187 - 191
Abstract
We propose a new algorithm for registering 3D scans obtained from different views of an object. Our work differs from the popular ICP based approach since we minimize error in signed distance function instead of squared distance between sampled surface points themselves. Our experiments show that this yields a fast and robust method of registering 3D scans into a single 3D model, firstly by simplifying point correspondence step, secondly by requiring fewer registration steps and lastly by using nonlinear optimization (the Levenberg-Marquardt algorithm) for error minimization, making the registration converge in fewer iterations. Our approach is also independent of the sampling resolution and works well in the presence of noise. We also believe that the distance-based error formulation lends itself much better for simultaneous registration of multiple overlapping views.
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Index Terms
- Multi-view 3D scanned data registration
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Published: 12 May 2008
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