TR2021-121
Graph Signal Processing for Geometric Data and Beyond: Theory and Applications
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- "Graph Signal Processing for Geometric Data and Beyond: Theory and Applications", IEEE Transactions on Multimedia, DOI: 10.1109/TMM.2021.3111440, Vol. 24, pp. 3961-3977, September 2021.BibTeX TR2021-121 PDF
- @article{Hu2021oct,
- author = {Hu, Wei and Pang, Jiahao and Liu, Xianming and Tian, Dong and Lin, Chia-Wen and Vetro, Anthony},
- title = {Graph Signal Processing for Geometric Data and Beyond: Theory and Applications},
- journal = {IEEE Transactions on Multimedia},
- year = 2021,
- volume = 24,
- pages = {3961--3977},
- month = sep,
- doi = {10.1109/TMM.2021.3111440},
- issn = {1941-0077},
- url = {https://www.merl.com/publications/TR2021-121}
- }
,
- "Graph Signal Processing for Geometric Data and Beyond: Theory and Applications", IEEE Transactions on Multimedia, DOI: 10.1109/TMM.2021.3111440, Vol. 24, pp. 3961-3977, September 2021.
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Abstract:
Geometric data acquired from real-world scenes, e.g., 2D depth images, 3D point clouds, and 4D dynamic point clouds, have found a wide range of applications including immersive telepresence, autonomous driving, surveillance, etc. Due to irregular sampling patterns of most geometric data, traditional image/video processing methodologies are limited, while Graph Signal Processing (GSP)—a fast-developing field in the signal processing community—enables processing signals that reside on irregular domains and plays a critical role in numerous applications of geometric data from low-level processing to high-level analysis. To further advance the research in this field, we provide the first timely and comprehensive overview of GSP methodologies for geometric data in a unified manner by bridging the connections between geometric data and graphs, among the various geometric data modalities, and with spectral/nodal graph filtering techniques. We also discuss the recently developed Graph Neural Networks (GNNs) and interpret the operation of these networks from the perspective of GSP. We conclude with a brief discussion of open problems and challenges.
Related Publication
- @article{Hu2020aug,
- author = {Hu, Wei and Pang, Jiahao and Liu, Xianming and Tian, Dong and Lin, Chia-Wen and Vetro, Anthony},
- title = {Graph Signal Processing for Geometric Data and Beyond: Theory and Applications},
- journal = {arXiv},
- year = 2020,
- month = aug,
- url = {https://arxiv.org/abs/2008.01918}
- }