动态小面积视觉目标跟踪判别算法及动物福利评价应用

Yu Wang, Jiandong Fang, Yudong Zhao
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引用次数: 0

摘要

智能牧场对牛福利状态的自动监测与评估,需要基于视频图像对目标牛的耳面积和形态进行跟踪识别。传统方法多采用接触检测,有一定的侵入性,容易引起牛的应激反应。本文设计了一种基于无标记姿态估计方法的动态小区域跟踪判别算法,该算法依次包括关键点跟踪匹配模型、牛耳相对波动模型和波动行为评价模型,最终实现了运动牛耳面积和形态特征的自动识别。通过仿真实验,验证了该方法的有效性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic small area visual target tracking discrimination algorithm and animal welfare evaluation applications
Automatic monitoring and evaluation of cattle welfare status in smart pastures requires tracking and identification of the target cattle's ear area and morphology based on video images. Most of the traditional methods use contact detection, which is somewhat invasive and easy to cause cattle stress reaction. In this paper, we design a dynamic small area tracking discrimination algorithm based on the marker less posture estimation method, which includes the tracking matching model of key points, the relative fluctuation model of cattle ear and the fluctuation behavior evaluation model in turn, and finally realize the automatic recognition of motion cattle ear area and morphological features. Through simulation experiments, the effectiveness and feasibility of the method are demonstrated.
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