Abstract
To address the surface reconstruction issue, this paper proposes an efficient and accurate approach for registration of multiview range scans. It has a good objective function designed, where all multiview registration parameters are involved. To solve this function, the coarse-to-fine approach is proposed, where each range scan should be sequentially registered to a coarse surface model, which is reconstructed by other scans with initial multiview alignment. By applying the trimmed iterative closest point algorithm, it can sequentially obtain good multiview registration results for each scan, which can then be immediately utilized to refine the coarse surface model for registration of other scans. To acquire accurate surface model, several rounds of update should be applied to all range scans involved in the multiview registration. With the increase of update round, it can finally obtain the accurate surface model. Experimental results on public data sets illustrate its superiority over previous approaches.
Highlights
Reconstructing three-dimensional (3-D) surface model is a fundamental and important issue in computer vision due to its wide application in reverse engineering, virtual reality, digital museums, prosthetic design, etc
Chetverikov et al proposed the trimmed iterative closest point (ICP) (TrICP) algorithm, which introduces an overlapping parameter into the objective function to discard outliers automatically.[5]
Given all multiview range scans acquired from one object, the alignment of scan pairs can be estimated by the approach presented in Ref. 8
Summary
Reconstructing three-dimensional (3-D) surface model is a fundamental and important issue in computer vision due to its wide application in reverse engineering, virtual reality, digital museums, prosthetic design, etc. The most popular solution to registration is iterative closest point (ICP) algorithm,[3,4] which can solve this problem for its good accuracy and fast speed. This approach cannot achieve the registration of partially overlapping range scans, which may arise in many practical applications. Different from previous works, this paper proposes a novel multiview registration approach for surface reconstruction. It first designs the objective function, where all registration parameters are involved.
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