基于YOLO v5+DeepSORT算法的羊群游走同步群体决策行为研究
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国家自然科学基金项目(32171963)


Experiment of Synchronized Group Decision-making Behavior under Herding Walk Model Based on YOLO v5+DeepSORT Algorithm
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    摘要:

    随着畜牧养殖智能化监控技术的产业化应用,进一步提升畜禽养殖的分类施策精细化管理,成为现代畜牧业精细高效养殖管理的新需求。采用固定机位、多角度视频采集技术,实时记录羊群牧食过程中的游走行为;针对羊群游走视频中易出现遮挡的复杂情况,设计了基于YOLO v5模型的羊群多目标检测模型,羊群游走过程中的多目标实时跟踪识别率可达90.63%;采用羊群游走多目标轨迹跟踪DeepSORT算法,通过提取羊目标的深度表观特征,计算出羊群游走轨迹和变化节拍规律。结果表明,羊的游走过程通常为慢走、快走和疾走3种方式,单只羊的游走过程通常是不固定的随机组合。在中大规模羊群中,由于亲缘关系结构的复杂性,羊群往往分化为多个小群体,这使得从整体上观察和分析羊群行为变得异常困难。为此,聚焦于小规模羊群进行研究,通过羊群散列、聚集和同步3个游走过程分析,初步验证了羊群游走节拍周期上的同步现象。

    Abstract:

    With the industrialized application of livestock breeding digital intelligent monitoring technology, further enhancement of the classification of livestock and poultry breeding policy fine management has become a new demand for fine and efficient breeding management in modern livestock industry. Adopting fixed camera position and multi-angle video acquisition technology, the wandering behavior of sheep in the process of grazing in real time was recorded;a multi-target detection model of sheep was designed based on YOLO v5 model, and multi-target real-time tracking and identification of sheep in the process of wandering was realized in response to the complex situation that was prone to be blocked in the video of sheep wandering, and the identification rate of small and medium-sized sheep can reach 90.63%.Then the DeepSORT algorithm was adopted for sheep wandering multi-target trajectory tracking, through extracting the depth of sheep target epigenetic features, the sheep wandering trajectory graph and the sheep wandering variable tempo change data were obtained. The experimental results showed that the wandering behaviors of sheep were usually in three different combinations: slow walking, fast walking and sprinting, and the wandering behaviors of a single sheep were usually in random combinations that were not fixed. In medium to large-scale sheep flocks, due to the complexity of their kinship structure, the flocks often differentiated into multiple small groups, which made it exceptionally difficult to observe and analyze their behavior holistically. In order to overcome this difficulty, it was turned to a small-scale target flock, and the synchronization phenomenon was initially verified on the beat cycle of sheep wandering through the empirical analysis of the three wandering processes of sheep dispersal, aggregation and synchronization.

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刘成,岳训.基于YOLO v5+DeepSORT算法的羊群游走同步群体决策行为研究[J].农业机械学报,2024,55(6):229-236. LIU Cheng, YUE Xun. Experiment of Synchronized Group Decision-making Behavior under Herding Walk Model Based on YOLO v5+DeepSORT Algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery,2024,55(6):229-236.

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  • 收稿日期:2023-11-02
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  • 在线发布日期: 2024-06-10
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