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    This study introduces HEVC-EPIC, a faster method for motion field estimation using coded motion information. It achieves comparable accuracy to existing techniques, enabling efficient video analysis and enhancement.

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    Area of Science:

    • Computer Vision
    • Video Processing
    • Signal Processing

    Background:

    • Optical flow estimation is crucial for video analysis.
    • Current methods often rely on time-consuming feature estimation.
    • Edge-preserving interpolation schemes (EPIC) create accurate motion fields.

    Purpose of the Study:

    • To develop a faster and efficient motion field estimation method.
    • To leverage High Efficiency Video Coding (HEVC) block motion for improved performance.
    • To integrate HEVC motion data into video analysis and enhancement tasks.

    Main Methods:

    • HEVC-EPIC derives motion seeds directly from decoded HEVC block motion, bypassing feature estimation.
    • Motion seed weighting strategies are employed to handle varying seed reliability.
    • The method utilizes an edge-preserving interpolation scheme (EPIC) for motion field generation.

    Main Results:

    • HEVC-EPIC significantly outperforms EPIC flow in speed.
    • It achieves a slightly lower average endpoint error (A-EPE) compared to EPIC flow.
    • In framerate upsampling, HEVC-EPIC yields slightly better Y-PSNR than EPIC flow.

    Conclusions:

    • HEVC-EPIC offers a computationally efficient alternative for high-quality motion field estimation.
    • The integration of HEVC motion data enhances video analysis and enhancement workflows.
    • This approach accelerates video processing tasks while maintaining high accuracy.