Point Cloud Quality Assessment Metric Based on Angular Similarity

The rise of immersive technologies has been recently fuelled by emerging applications which employ advanced content representations. Among various alternatives, point clouds denote a promising solution which has recently drawn a significant amount of interest, as witnessed by the latest activities of standardization committees. However, subjective and objective quality assessments for this type of content still remain an open problem. In this paper, we introduce a simple yet efficient objective metric to capture perceptual degradations of a distorted point cloud. Correlation with subjective quality assessment scores carried out by human subjects shows the proposed metric to be superior to the state of the art in terms of predicting the visual quality of point clouds under realistic types of distortions, such as octree-based compression.


Publié dans:
2018 IEEE International Conference on Multimedia and Expo (ICME)
Présenté à:
2018 IEEE International Conference on Multimedia and Expo (ICME), San Diego, California, USA, July 23-27, 2018
Année
2018
ISBN:
978-1-5386-1737-3
Mots-clefs:
Laboratoires:




 Notice créée le 2018-04-17, modifiée le 2019-06-19

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