Efficient Deep-Based Graph Metric for Point Cloud Quality Assessment
In: International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023) ; https://hal.science/hal-04026860 ; International Conference on Acoustics, 2023
Online
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Zugriff:
International audience ; Following the advent of immersive technologies and the increasing interest in representing interactive geometrical format, 3D Point Clouds (PC) have emerged as a promising solution and effective means to display 3D visual information. In addition to other challenges in immersive applications, objective and subjective quality assessments of compressed 3D content remain open problems and an area of research interest. Yet most of the efforts in the research area ignore the local geometrical structures between points representation. In this paper, we overcame previous limitation by introducing a novel and efficient objective metric for Point Clouds Quality Assessment, throughout learning local intrinsic dependencies using Graph Neural Network (GNN). To evaluate the performance of our method, two well-known datasets have been used. The results demonstrate the effectiveness and reliability of our solution compared to state-of-the-art metrics.
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Efficient Deep-Based Graph Metric for Point Cloud Quality Assessment
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Autor/in / Beteiligte Person: | Tliba, Marouane ; Chetouani, Aladine ; Valenzise, Giuseppe ; Dufaux, Frédéric ; Laboratoire pluridisciplinaire de recherche en ingénierie des systèmes, mécanique et énergétique (PRISME) ; Université d'Orléans (UO)-Institut National des Sciences Appliquées - Centre Val de Loire (INSA CVL) ; Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA) ; Laboratoire des signaux et systèmes (L2S) ; Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS) ; CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) ; IEEE |
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Zeitschrift: | International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023) ; https://hal.science/hal-04026860 ; International Conference on Acoustics, 2023 |
Veröffentlichung: | HAL CCSD, 2023 |
Medientyp: | Konferenz |
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