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Proceedings Paper

On the performance of metrics to predict quality in point cloud representations
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Paper Abstract

Point clouds are a promising alternative for immersive representation of visual contents. Recently, an increased interest has been observed in the acquisition, processing and rendering of this modality. Although subjective and objective evaluations are critical in order to assess the visual quality of media content, they still remain open problems for point cloud representation. In this paper we focus our efforts on subjective quality assessment of point cloud geometry, subject to typical types of impairments such as noise corruption and compression-like distortions. In particular, we propose a subjective methodology that is closer to real-life scenarios of point cloud visualization. The performance of the state-of-the-art objective metrics is assessed by considering the subjective scores as the ground truth. Moreover, we investigate the impact of adopting different test methodologies by comparing them. Advantages and drawbacks of every approach are reported, based on statistical analysis. The results and conclusions of this work provide useful insights that could be considered in future experimentation.

Paper Details

Date Published: 19 September 2017
PDF: 16 pages
Proc. SPIE 10396, Applications of Digital Image Processing XL, 103961H (19 September 2017); doi: 10.1117/12.2275142
Show Author Affiliations
Evangelos Alexiou, Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Touradj Ebrahimi, Ecole Polytechnique Fédérale de Lausanne (Switzerland)

Published in SPIE Proceedings Vol. 10396:
Applications of Digital Image Processing XL
Andrew G. Tescher, Editor(s)

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