Abstract

In this paper, a process for high-resolution, automated 3D digitization of unknown objects (i.e., without any digital model) is presented. The process has two stages—the first leads to a coarse 3D digital model of the object, and the second obtains the final model. A rough model, acquired by a 3D measurement head with a large working volume and relatively low resolution, is used to calculate the precise head positions required for the full digitization of the object, as well as collision detection and avoidance. We show that this approach is much more efficient than digitization with only a precise head, when its positions for subsequent measurements (so-called next-best-views) must be calculated based only on a partially recovered 3D model of the object. We also show how using a rough object representation for collision detection shortens the high-resolution digitization process.

© 2016 Optical Society of America

Guide to quickly build high-quality three-dimensional models with a structured light range scanner

Bao-Quan Shi and Jin Liang
Appl. Opt. 55(36) 10158-10169 (2016)

Automated measurement method for 360° profilometry of 3-D diffuse objects

Xiao-Xue Cheng, Xian-Yu Su, and Lu-Rong Guo
Appl. Opt. 30(10) 1274-1278 (1991)

Automated 360° profilometry of 3-D diffuse objects

Maurice Halioua, Ravi S. Krishnamurthy, Hsin-Chu Liu, and Fu-Pen Chiang
Appl. Opt. 24(14) 2193-2196 (1985)

Automated phase-measuring profilometry of 3-D diffuse objects

V. Srinivasan, H. C. Liu, and M. Halioua
Appl. Opt. 23(18) 3105-3108 (1984)

3D-imaging: a scanning light pattern projector

Mathias Bøgh Stokholm, Steen Grüner Hanson, Rasmus Kjær, Thomas Allin, and Michael Linde Jakobsen
Appl. Opt. 55(32) 9074-9083 (2016)