A Streaming Technology of 3D Design and Manufacturing Visualization Information Sharing for Cloud-Based Collaborative Systems

  • Weidong LiEmail author
  • Y. L. Cai
  • W. F. Lu
Part of the Springer Series in Advanced Manufacturing book series (SSAM)


One of the challenging problems that hinder the development of Cloud-based collaborative systems is the contradiction of large design or manufacturing visualization data and the limited bandwidth of the Internet and Web to share the data remotely to support collaborative work. Faster visualization of design and manufacturing models during collaboration has been needed for a long time. Recently, a new scheme for visualization has been presented, viz., the 3D streaming technology. 3D streaming technique can allow effective dispatch and access of large-volume design and manufacturing data as a series of patched streams across the Internet, and therefore provide a promising solution to overcome the obstacle. The key technology to realize the streaming technique is geometric simplification (or decimation) of 3D models. In this chapter, a new streaming technology based on a geometric simplification algorithm has been developed, in which two criteria are the crucial elements to control the collapse process for edges in 3D visualization models represented in VRML. After the simplification and sharing of a model, a developed refinement algorithm is carried out to restore the model from its simplified version back to its original, through combining the simplified model with some reconstruction data generated during the simplification process, therefore, to realize the streaming information sharing. The major feature of the streaming algorithm is that it has incorporated some advantages of the previously developed vertex decimation approach and edge collapse approach. Meanwhile, the mechanism of adaptive threshold parameters adopted in this work enhances the adaptability of the algorithm for various applications. Case studies and comparisons with some related works have been carried out to demonstrate the performance and potentials of the algorithm in terms of efficiency, adaptability and robustness.


Geometric Error Virtual Reality Modeling Language Vertex Pair Simple Vertex Corner Vertex 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  1. 1.Faculty of Engineering and ComputingCoventry UniversityCoventryUK
  2. 2.Singapore-MIT Alliance, Innovative Manufacturing System and Technology ProgramNational University of SingaporeSingaporeSingapore

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