Efficient view-dependent LOD control for large 3D unclosed mesh models of environments

The rapid progress of 3D modeling techniques have brought more and more applications of 3D range data in robotics. However, the 3D data we acquire with range finders mounted on mobile robots are usually too large to process in real-time, and holes and boundaries are unavoidable on the surface it represents. One method to resolve this problem is to perform mesh simplification and level of detail (LOD) control on these models. A new method based on progressive meshes (PMs) is proposed in this paper, which adopts different simplification and remeshing strategies on different boundary conditions, and therefore well preserves geometrical features on the boundaries through the simplification. The detail records are organized in a forest-shaped data structure at the same time. Hence, when a scene is reconstructed using the multiresolution models, the local details can be rapidly added by selective refinement. Furthermore, continuous view-dependent distributions of LOD are also supported to provide efficient scene representation and rendering.

[1]  Enrico Puppo,et al.  Building and traversing a surface at variable resolution , 1997 .

[2]  Christian Früh,et al.  3D model generation for cities using aerial photographs and ground level laser scans , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[3]  Peter Lindstrom,et al.  Fast and memory efficient polygonal simplification , 1998, Proceedings Visualization '98 (Cat. No.98CB36276).

[4]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[5]  Yasushi Yagi,et al.  Resolution improving method for a 3D environment modeling using omnidirectional image sensor , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[6]  Ioannis Stamos,et al.  AVENUE: Automated site modeling in urban environments , 2001, Proceedings Third International Conference on 3-D Digital Imaging and Modeling.

[7]  W. W. Armstrong,et al.  Single Camera Stereo for Mobile Robot World Exploration , 1999 .

[8]  M. Garland,et al.  Multiresolution Modeling: Survey & Future Opportunities , 1999 .

[9]  Martial Hebert,et al.  Unconstrained registration of large 3D point sets for complex model building , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[10]  Peter K. Allen,et al.  A robotic system for 3D model acquisition from multiple range images , 1997, Proceedings of International Conference on Robotics and Automation.

[11]  Joachim Hertzberg,et al.  Automatic model refinement for 3D reconstruction with mobile robots , 2003, Fourth International Conference on 3-D Digital Imaging and Modeling, 2003. 3DIM 2003. Proceedings..

[12]  Leila De Floriani,et al.  Building and traversing a surface at variable resolution , 1997, Proceedings. Visualization '97 (Cat. No. 97CB36155).

[13]  Sebastian Thrun,et al.  Real-time acquisition of compact volumetric 3D maps with mobile robots , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[14]  Charles Q. Little,et al.  Rapid world modeling: fitting range data to geometric primitives , 1997, Proceedings of International Conference on Robotics and Automation.

[15]  Michael Garland,et al.  Multiresolution Modeling: Survey and Future Opportunities , 1999, Eurographics.

[16]  Hugues Hoppe,et al.  View-dependent refinement of progressive meshes , 1997, SIGGRAPH.

[17]  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).

[18]  Tony DeRose,et al.  Mesh optimization , 1993, SIGGRAPH.

[19]  Hugues Hoppe,et al.  Progressive meshes , 1996, SIGGRAPH.

[20]  Michael Garland,et al.  Surface simplification using quadric error metrics , 1997, SIGGRAPH.

[21]  Don Ray Murray,et al.  Using Real-Time Stereo Vision for Mobile Robot Navigation , 2000, Auton. Robots.

[22]  Wolfram Burgard,et al.  Mobile robot mapping in populated environments , 2003, Adv. Robotics.

[23]  Sebastian Thrun,et al.  Learning to Locate an Object in 3D Space from a Sequence of Camera Images , 1998, ICML.