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    A new database of dynamic colored meshes (DCM) with distortions was created to assess perceptual quality. This resource aids in developing objective metrics and improving DCM compression techniques.

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    Area of Science:

    • Computer graphics
    • Multimedia processing
    • Perceptual quality assessment

    Background:

    • Dynamic colored meshes (DCM) are prevalent in various applications but susceptible to distortions during compression or transmission, degrading quality.
    • Objective metrics are needed to evaluate DCM quality, but existing databases are limited.

    Purpose of the Study:

    • To create a comprehensive database of distorted DCMs for perceptual quality research.
    • To facilitate the development and evaluation of objective quality metrics for DCMs.
    • To provide recommendations for DCM compression and quality assessment.

    Main Methods:

    • Creation of the Tencent - Dynamic colored Mesh Database (TDMD) with eight reference DCMs and six distortion types.
    • Generation of 303 distorted DCM samples using processed video sequences (PVS).
    • Conducting a large-scale subjective experiment to obtain Mean Opinion Scores (MOS).
    • Evaluation of three types of state-of-the-art objective metrics (image-based, point-based, video-based).

    Main Results:

    • The TDMD is the largest available DCM database, containing 303 distorted samples with MOS.
    • Subjective experiments reveal the perceptual impact of different distortion types on DCMs.
    • Evaluation highlights the strengths and weaknesses of current objective metrics for DCM quality assessment.

    Conclusions:

    • The TDMD provides a valuable resource for studying DCM distortion perception and developing objective metrics.
    • Recommendations are offered for selecting appropriate objective metrics in practical DCM applications.
    • The database supports advancements in DCM compression and quality evaluation.