Towards A Colored Point Cloud Quality Assessment Method Using Colored Texture And Curvature Projection

Colored point cloud (PC) provides convenience for 3D digitization in the real world, but its huge amount of data needs to be compressed effectively. However, lossy compression will bring visual quality problems, so it is necessary to design reliable quality assessment methods. Considering the visual connection between 3D space and projection plane, we propose a new PC quality assessment (PCQA) method combining colored texture and curvature projection in this paper. Specifically, the colored texture information and curvature of colored PC are projected onto 2D planes to extract texture and geometric statistical features, respectively, so as to characterize the texture and geometric distortion. Experimental results on two colored PC databases (CPCD2.0 and IRPC) show that the proposed method has a good correlation with subjective quality scores and is superior to the state-of-the-art PCQA methods.