Article ID Journal Published Year Pages File Type
527834 Computer Vision and Image Understanding 2012 13 Pages PDF
Abstract

Several methods perform the integration of multiple range scans of an object aiming the generation of a reconstructed triangle mesh; however, achieving high fidelity digital reconstructions is still a challenge. That is mostly due to the existence of outliers in the acquired range data, and their harmful effects on the integration algorithms. In this work, we first discuss artifacts usually found on real range data captured with 3D scanners based on laser triangulation. Following that there is the assessment of two widely used volumetric integration techniques (VRIP and Consensus Surface) and our suggested improvements. We also present a novel, hybrid approach that combines strengths from both VRIP and Consensus Surface, named IMAGO Volumetric Integration Algorithm (IVIA). Our novel algorithm adds new ideas while improving the detection and elimination of artifacts. Further, IVIA works in close cooperation with the subsequent hole filling process, which greatly improves the overall quality of the generated 3D models. Our technique leads to better results when assessed in different situations, when compared to VRIP, Consensus Surface, and also to a well known state-of-the-art surface-based method, Poisson Surface Reconstruction.

► We discuss artifacts found on real range data captured with 3D scanners. ► We assess two widely used algorithms, VRIP and Consensus Surfaces, and suggest improvements. ► We present a novel, hybrid algorithm (IVIA) that greatly improve the detection and elimination of artifacts. ► We show that IVIA works in close cooperation with the hole filling process, improving the overall quality of the 3D models. ► We show that IVIA yields high fidelity 3D reconstructions applied to the digital preservation of cultural heritages.

Related Topics
Physical Sciences and Engineering Computer Science Computer Vision and Pattern Recognition
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