Linear-time compression of 2-manifold polygon meshes into information-theoretically optimal number of bits

Lyuu, Yuh‐Dauh; Ma, Tak-Man; Ti, Yen‐Wu

doi:10.1016/j.amc.2011.03.040

Cited by 1 publication

(2 citation statements)

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“…The diagonal value in Σ is defined in (8), λ i is the eigenvalue of A. Σ ii =√λ i (8) The diagonal value Σ ii decreases in descending order, then truncate the small eigenvalues of Σ and store the result in Σ + , as shown in (9).…”

Section: 22mentioning

confidence: 99%

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A 3D Model Compression Method for Large Scenes

Zhou¹,

Wang²,

Ding³

et al. 2018

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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Three-dimensional (3D) models are increasingly becoming an important tool in project management. At the same time, the 3D data of construction industry is more and more large, whether it is caused by large model scene or the requirement of model accuracy. In order to meet the requirements of the model application, the 3D model needs to be simplified. Mesh models are one of the most common ways to display 3D models, which provide well-defined object boundaries. The simplified algorithm of the existing mesh model cannot keep the important detail features of the original model once the data volume of the model is further reduced. Combined with Quadric Error Metrics (QEM) algorithm, this paper improves the edge collapse algorithm to solve the problem of undetected model structure and oversimplified model details. The proposed algorithm can preserve the integrity of the model while maintaining a high compression efficiency. Experiments show that the proposed method works well for the compression of large-scale scene models, which includes the compression ratio and the structural preservation in the model. This compression method is well suited for the model with huge amounts of data generated by large scene objects in the construction field.

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Section: 22mentioning

confidence: 99%

“…Later, the compression of the mesh model evolved. For the current research, the simplified algorithm still deserves further study in the relatively large 3D model, no matter in the compression effect or in the compression time [9].…”

Section: Introductionmentioning

confidence: 99%