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Article Dans Une Revue IEEE Transactions on Multimedia Année : 2024

BASICS: Broad Quality Assessment of Static Point Clouds in a Compression Scenario

Résumé

Point clouds have become increasingly prevalent in representing 3D scenes within virtual environments, alongside 3D meshes. Their ease of capture has facilitated a wide array of applications on mobile devices, from smartphones to autonomous vehicles. Notably, point cloud compression has reached an advanced stage and has been standardized. However, the availability of quality assessment datasets, which are essential for developing improved objective quality metrics, remains limited. In this paper, we introduce BASICS, a large-scale quality assessment dataset tailored for static point clouds. The BASICS dataset comprises 75 unique point clouds, each compressed with four different algorithms including a learning-based method, resulting in the evaluation of nearly 1500 point clouds by 3500 unique participants. Furthermore, we conduct a comprehensive analysis of the gathered data, benchmark existing point cloud quality assessment metrics and identify their limitations. By publicly releasing the BASICS dataset, we lay the foundation for addressing these limitations and fostering the development of more precise quality metrics.
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Dates et versions

hal-04280304 , version 1 (10-11-2023)
hal-04280304 , version 2 (19-01-2024)

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Citer

Ali Ak, Emin Zerman, Maurice Quach, Aladine Chetouani, Aljosa Smolic, et al.. BASICS: Broad Quality Assessment of Static Point Clouds in a Compression Scenario. IEEE Transactions on Multimedia, 2024, 26, pp.6730-6742. ⟨10.1109/TMM.2024.3355642⟩. ⟨hal-04280304v2⟩
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