Abstract:
This paper presents an analysis of the performance of point cloud-based and image-based quality metrics on dynamic point clouds, based on subjective quality assessment of...Show MoreMetadata
Abstract:
This paper presents an analysis of the performance of point cloud-based and image-based quality metrics on dynamic point clouds, based on subjective quality assessment of their geometry-only and textured versions. The subjective quality assessment was conducted as an expert viewing with 2D video representations of the point clouds using pre-defined camera paths for rendering. It is considered to be a first-time experiment assessing geometry-only rendering with dynamic point-clouds. The study includes correlation measures and a statistical analysis on the reliability of objective metrics. The suitability of the metrics for the evaluation task and the subjective assessment of the geometry-only case are discussed. The results indicate that geometry-based PSNRY as well as image-based metrics can provide reliable results for textured point clouds. Based on the subjective results, the objective assessment of geometry-only point clouds is found to be less reliable than for the textured ones. Other findings report a divergence between results of the geometry-based D1 and D2 metrics and the subjective impact of geometry errors.
Date of Conference: 08-11 September 2024
Date Added to IEEE Xplore: 10 December 2024
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