IEEE Access (Jan 2024)

Alignment and Improvement of Shape-From-Silhouette Reconstructed 3D Objects

  • Alberto J. Perez,
  • Javier Perez-Soler,
  • Juan-Carlos Perez-Cortes,
  • Jose-Luis Guardiola

DOI
https://doi.org/10.1109/ACCESS.2024.3407341
Journal volume & issue
Vol. 12
pp. 76975 – 76985

Abstract

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3D object alignment is essential in multiple fields. For instance, to allow precise measurements in metrology, to perform surface/volumetric checks or quality control in industrial inspection, to align partial captures of a 3D object during object scanning, to simplify object recognition or classification in pattern recognition, accuracy and speed, being opposed, are desirable features of those algorithms. Nevertheless, they can be more or less critical depending on the application area. In the present work, we propose a methodology to improve the alignment of 3D objects reconstructed using shape-from-silhouette techniques. This reconstruction technique produces objects with small synthetic bulges, making them more difficult to align accurately. On the one hand, prealignment and branch-and-bound techniques are used to improve the convergence and speed of the alignment algorithms. On the other hand, a method to obtain a precise alignment even in the presence of bulges is presented. Finally, a refinement of the shape-from-silhouettes technique is shown. This technique uses multiple captures to refine object reconstruction and reduce or eliminate, among other improvements, synthetic bulges.

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