MACHINE LEARNING BASED SYSTEM AND METHOD FOR CONTROLLING RESIDUAL ARTIFACTS IN MEDIA CONTENTS TO OPTIMIZE USER EXPERIENCE IN REAL-TIME SCREEN-TO-CAMERA COMMUNICATION ENVIRONMENT

    公开(公告)号:US20250030811A1

    公开(公告)日:2025-01-23

    申请号:US18780539

    申请日:2024-07-23

    Abstract: A machine learning based system and method for controlling residual artifacts in media contents to optimize user experience in real-time screen-to-camera communication environment, is disclosed. The machine learning based method includes converting RGB values of pixels to values of orthogonal or perceptual color space values for pixels; segmenting intensities of frames associated with the media contents, into bright, dark, and middle regions; generating symbols comprising optimized-frequency regions using a machine learning model; setting width border of boundaries to pre-determined pixel values for encoding ACR data; dividing the boundaries into boxes to embed information associated with symbols; assigning a bit value of one to boxes comprising first pre-determined sizes, and a bit value of zero to the boxes comprising second pre-determined sizes; assembling boxes within interior of frames; and controlling the residual artifacts of an encoding process in the media contents by reducing modulation depth based on the optimized redundancy.

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