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

Autor: Alberto J. Perez, Javier Perez-Soler, Juan-Carlos Perez-Cortes, Jose-Luis Guardiola
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: IEEE Access, Vol 12, Pp 76975-76985 (2024)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2024.3407341
Popis: 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.
Databáze: Directory of Open Access Journals