Multi-stream POINTNet-based Model For Blind Geometric Point Cloud Quality Assessment
Résumé
The evaluation of 3D point cloud quality is a critical com-
ponent in the development of immersive multimedia systems
for real-world applications. While perceptual quality evalua-
tion techniques for 2D images and videos have reached high
performances, developing robust and efficient blind metrics
for point cloud quality assessment is still challenging. In
this paper, we propose a no-reference point cloud quality as-
sessment method that evaluates the quality of degraded 3D
objects using an end-to-end multi-stream point-based model.
We introduce geometric coordinates, normals, and curvatures
as inputs to the proposed model stream to extract significant
degradation features that are incorporated to predict the vi-
sual quality of 3D point clouds. Experimental results on two
benchmark databases: ICIP202 and SJTU, demonstrate that
the proposed model achieves promising performance com-
pared to state-of-the-art full and reduced methods.