Subjective and objective quality evaluation of compressed point clouds

2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX)

Ebrahimi

2019

Point clouds are a new modality for representation of plenoptic content and a popular alternative to create immersive media. Despite recent progress in capture, display, storage, delivery and processing, the problem of a reliable approach to subjectively and objectively assess the quality of point clouds is still largely open. In this study, we extend the state of the art in projection-based objective quality assessment of point cloud imaging by investigating the impact of the number of viewpoints employed to assess the visual quality of a content, while discarding information that does not belong to the object under assessment, such as background color. Additionally, we propose assigning weights to the projected views based on interactivity information, obtained during subjective evaluation experiments. In the experiment that was conducted, human observers assessed a carefully selected collection of typical contents, subject to geometry and color degradations due to compression. The point cloud models were rendered using cubes as primitive elements with adaptive sizes based on local neighborhoods. Our results show that employing a larger number of projected views does not necessarily lead to better predictions of visual quality, while user interactivity information can improve the performance.

Section: Introductionmentioning

confidence: 99%

Exploiting user interactivity in quality assessment of point cloud imaging

2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX)

Ebrahimi

2019

“…In [7] and [8], PCs rendered as surfaces, employing the same surface reconstruction technique [6], were visualized and assessed in 2D and 3D monitors, respectively, 978-1-5386-8212-8/19/$31.00 ©2019 IEEE following a passive evaluation. In [9], subjective and objective quality assessment of PCs degraded by compression artifacts was performed. The most popular objective quality metrics were benchmarked against human judgments obtained from the subjective experiment.…”

Section: Introductionmentioning

confidence: 99%

Point cloud quality evaluation: Towards a definition for test conditions

Cruz

Dumic

2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX)

et al. 2019

Recently stakeholders in the area of multimedia representation and transmission have been looking at plenoptic technologies to improve immersive experience. Among these technologies, point clouds denote a volumetric information representation format with important applications in the entertainment, automotive and geographical mapping industries. There is some consensus that state-of-the-art solutions for efficient storage and communication of point clouds are far from satisfactory. This paper describes a study on point cloud quality evaluation, conducted in the context of JPEG Pleno to help define the test conditions of future compression proposals. A heterogeneous set of static point clouds in terms of number of points, geometric structure and represented scenarios were selected and compressed using octree-pruning and a projection-based method, with three different levels of degradation. The models were comprised of both geometrical and color information and were displayed using point sizes large enough to ensure observation of watertight surfaces. The stimuli under assessment were presented to the observers on 2D displays as animations, after defining suitable camera paths to enable visualization of the models in their entirety and realistic consumption. The experiments were carried out in three different laboratories and the subjective scores were used in a series of correlation studies to benchmark objective quality metrics and assess inter-laboratory consistency.

“…However, the impact of visualizing reconstructed meshes instead of raw PCs was not investigated. In [5], subjective quality assessment of colored PCs was conducted, subject to simple octree and graph-based encoding algorithms. To render the PC data, primitive cubes were used.…”

Section: Introductionmentioning

confidence: 99%

Point Cloud Subjective Evaluation Methodology based on 2D Rendering

2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)

Ebrahimi

Bernardo

et al. 2018

Abstract-Point clouds are one of the most promising technologies for 3D content representation. In this paper, we describe a study on quality assessment of point clouds, degraded by octreebased compression on different levels. The test contents were displayed using Screened Poisson surface reconstruction, without including any textural information, and they were rated by subjects in a passive way, using a 2D image sequence. Subjective evaluations were performed in five independent laboratories in different countries, with the inter-laboratory correlation analysis showing no statistical differences, despite the different equipment employed. Benchmarking results reveal that the state-of-the-art point cloud objective metrics are not able to accurately predict the expected visual quality of such test contents. Moreover, the subjective scores collected from this experiment were found to be poorly correlated with subjective scores obtained from another test involving visualization of raw point clouds. These results suggest the need for further investigations on adequate point cloud representations and objective quality assessment tools.