Embedded Deformation-Based Compression for Human 3D Dynamic Meshes with Changing Topology

Huong Hoang, Kunyao Chen, Truong Nguyen, Pamela C. Cosman

ICCVW 2023 pp. 2244-2254

doi:10.1109/ICCVW60793.2023.00239 /iccvw/2023/hoang2023iccvw-embedded/

Abstract

3D dynamic meshes offer significant potential in various applications, but their usage is still limited by their large file size. We present a novel method that can compress 3D human dynamic meshes effectively by using embedded deformation to extract the underlying transformations of consecutive frames. We target 3D dynamic meshes with changing connectivity which are more versatile compared to traditional mesh animation but also more challenging. To further reduce the transmission size, we propose a novel optimization-based technique to determine a sparse set of key nodes capable of transmitting the transformations efficiently.

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Cite

Text

Hoang et al. "Embedded Deformation-Based Compression for Human 3D Dynamic Meshes with Changing Topology." IEEE/CVF International Conference on Computer Vision Workshops, 2023. doi:10.1109/ICCVW60793.2023.00239

Markdown

[Hoang et al. "Embedded Deformation-Based Compression for Human 3D Dynamic Meshes with Changing Topology." IEEE/CVF International Conference on Computer Vision Workshops, 2023.](https://mlanthology.org/iccvw/2023/hoang2023iccvw-embedded/) doi:10.1109/ICCVW60793.2023.00239

BibTeX

@inproceedings{hoang2023iccvw-embedded,
  title     = {{Embedded Deformation-Based Compression for Human 3D Dynamic Meshes with Changing Topology}},
  author    = {Hoang, Huong and Chen, Kunyao and Nguyen, Truong and Cosman, Pamela C.},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2023},
  pages     = {2244-2254},
  doi       = {10.1109/ICCVW60793.2023.00239},
  url       = {https://mlanthology.org/iccvw/2023/hoang2023iccvw-embedded/}
}