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This research study utilizes computer vision to estimate multi-person human pose from real-time and pre-recorded video. Computer vision examines human posture detection from RGB images. The proposed method works well for gesture control, gaming, human tracking, action detection, and action tracking. Tracking semantic important points is pose estimation. Two-dimensional human pose estimation predicts the spatial placement of key human body points from images and videos. Several anatomical areas use hand-crafted feature extraction methods to estimate two-dimensional human position. Visual input data and human body component locations are used to estimate human pose. OpenCV and Mediapipe detected 33 posture landmarks in our research. Estimating human body state requires modeling. Model-based methods are used to describe and infer human posture in 2D or 3D. This research uses the …