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Walking Posture Analysis of Pigs Based on Star Skeleton Model

机译:基于明星骨架模型的猪行走姿态分析

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In order to make better use of video image processing technology to monitor and analyze behaviors of animals, a new walking posture analysis method based on star skeleton is proposed. Firstly, a pig target is detected and its boundary is extracted from the images. Secondly, according to the target's boundary the center of mass is computed and the curve of distance between contour points and center of mass is draw. The extremums of the above curve are computed to obtain the key contour points from the curve. The stick model of pigs is built by connecting the key contour points with its center of mass. Finally, the gaits of pigs are recognized by analyzing cyclic motion of the key contour points in the stick model. More specifically, the foreleg walking frequency of pigs could be calculated using the spectrum analysis method. The experiments results indicate that this method has higher recognition accuracy for the walking gaits of pigs. The relative error of the results is only within 10%. Furthermore, compared with manual monitoring method, it is more objective and convenient. Thus, this algorithm provides a new solution for animal behavior analysis based on video surveillance and image processing.
机译:为了更好地利用视频图像处理技术来监测和分析动物的行为,提出了一种基于星骨架的新的行走姿势分析方法。首先,检测到猪目标,并从图像中提取其边界。其次,根据目标的边界,计算骨骼中心,轮廓点与质心之间的距离曲线是抽取的。计算上述曲线的极端,以获得来自曲线的键轮廓点。通过将钥匙轮廓点与其质量中心连接来构建猪的棒模型。最后,通过分析棒模型中的键轮廓点的循环运动来识别猪的婴儿空间。更具体地,可以使用频谱分析方法计算猪的前肢步行频率。实验结果表明,该方法具有较高的猪行走仪的识别准确性。结果的相对误差仅在10%以内。此外,与手动监测方法相比,更客观方便。因此,该算法为基于视频监控和图像处理的动物行为分析提供了新的解决方案。

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