Dual-beam structured-light scanning for 3-D object modeling

In this paper we present our Dual-Beam Structured-Light Scanner (DSLS), a scanning system that generates range maps much richer than those obtained from a conventional structured-light scanning system. Range maps produced by DSLS require fewer registrations for 3-D modeling. We show that the DSLS system more easily satisfies what are often difficult-to-satisfy conditions for determining the 3-D coordinates of an arbitrary object point. Two specific advantages of DSLS over conventional structured-light scanning are: (1) A single scan by the DSLS system is capable of generating range data on more surfaces than possible with the conventional approach using the same number of camera images. And (2) since the data collected by DSLS is more free of self-occlusions, the object needs be examined from a smaller number of viewpoints.

[1]  Je L. EdwardsRobot Experimental State of the Art in 3d Object Recognition and Localization Using Range Data , 1995 .

[2]  Martial Hebert,et al.  Large data sets and confusing scenes in 3-D surface matching and recognition , 1999, Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062).

[3]  Hongbin Zha,et al.  Dynamic gaze-controlled levels of detail of polygonal objects in 3-D environment modeling , 1999, Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062).

[4]  Marc Levoy,et al.  The digital Michelangelo project: 3D scanning of large statues , 2000, SIGGRAPH.

[5]  Katsushi Ikeuchi,et al.  Appearance compression and synthesis based on 3D model for mixed reality , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[6]  Andrew E. Johnson,et al.  Surface matching for object recognition in complex three-dimensional scenes , 1998, Image Vis. Comput..

[7]  Charles V. Stewart,et al.  Fast and robust registration of 3D surfaces using low curvature patches , 1999, Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062).

[8]  Gérard G. Medioni,et al.  Object modelling by registration of multiple range images , 1992, Image Vis. Comput..

[9]  Robert Bergevin,et al.  Towards a General Multi-View Registration Technique , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Ioannis Stamos,et al.  3-D modeling from range imagery: an incremental method with a planning component , 1997, Proceedings. International Conference on Recent Advances in 3-D Digital Imaging and Modeling (Cat. No.97TB100134).

[11]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Avinash C. Kak,et al.  Modeling and calibration of a structured light scanner for 3-D robot vision , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[13]  Hongbin Zha,et al.  Active modeling of 3-D objects: planning on the next best pose (NBP) for acquiring range images , 1997, Proceedings. International Conference on Recent Advances in 3-D Digital Imaging and Modeling (Cat. No.97TB100134).

[14]  Chia-Chen Chen,et al.  A 3D scanning system based on low-occlusion approach , 1999, Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062).