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Multi-stream Point-based model for Blind Geometric Point Cloud Quality Assessment

Published: 30 December 2023 Publication History

Abstract

The evaluation of 3D point cloud quality is a critical component in the development of immersive multimedia systems for real-world applications. While perceptual quality evaluation technics for 2D images and videos have reached high performances, developing robust and efficient blind metrics for point cloud quality assessment is still challenging. In this paper, we propose a no-reference point cloud quality assessment method that evaluates the quality of degraded 3D objects using an end-to-end point-based multi-stream model. To capture the geometric degradation of the point cloud, we incorporate normals, curvatures and geometric coordinates. Then, we divide the distorted object into sub-objects, which are fed to a multi-stream network to extract significant features of the geometric degradation. Afterward, these features are used to predict the quality of each sub-object, and the perceptual quality score of the point cloud is obtained by averaging the quality scores of all sub-objects. Experimental results demonstrate that the proposed model achieves promising performance compared to state-of-the- art full and reduced methods.

References

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    CBMI '23: Proceedings of the 20th International Conference on Content-based Multimedia Indexing
    September 2023
    274 pages
    ISBN:9798400709128
    DOI:10.1145/3617233
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 30 December 2023

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    Author Tags

    1. 3D point cloud
    2. Deep learning.
    3. Multi-stream
    4. Point-based model
    5. Quality assessment

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