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Remarks on Human Body Posture Estimation From Silhouette Image Based on Heuristic Rules and Kalman Filter

机译:基于启发式规则和卡尔曼滤波的轮廓图像人体姿态估计

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This paper proposes a human body posture estimation method based on analysis of human silhouette and Kalman filter. The proposed method is based on both the heuristically extraction method of estimating the significant points of human body and the contour analysis of the human silhouette. The 2D coordinates of the human body's significant points, such as top of the head, and tips of feet, are located by applying the heuristically extraction method to the human silhouette, those of tips of hands are obtained by using the result of the contour analysis, and the joints of elbows and knees are estimated by introducing some heuristic rules to the contour image of the human silhouette. The estimated results are optimized and tracked by using Kalman filter. The proposed estimation method is implemented on a personal computer and runs in real-time. Experimental results show both the feasibility and the effectiveness of the proposed method for estimating human body postures.
机译:提出了一种基于人体轮廓分析和卡尔曼滤波的人体姿态估计方法。所提出的方法基于估计人体重要点的启发式提取方法和人体轮廓的轮廓分析。通过将启发式提取方法应用于人体轮廓,可以定位人体重要点(例如头顶和脚尖)的2D坐标,而轮廓分析的结果则可以得出手尖的2D坐标,并通过在人体轮廓的轮廓图像中引入一些启发式规则来估计肘部和膝盖的关节。使用卡尔曼滤波器对估计结果进行优化和跟踪。所提出的估计方法在个人计算机上实现并实时运行。实验结果表明了该方法在人体姿态估计中的可行性和有效性。

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