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Motion-Status-Driven Piglet Tracking Method for Monitoring Piglet Movement Patterns Under Sow Posture Changes

文献类型： 外文期刊

作者： Yang, Aqing 1 ; Li, Shimei 2 ; Tu, Shuqin 3 ; Han, Na 1 ; Zhang, Lei 1 ; Luo, Yizhi 4 ; Xue, Yueju 5 ;

作者机构： 1.Guangdong Polytech Normal Univ, Coll Comp Sci, Guangzhou 510665, Peoples R China

2.Guangzhou Kingmed Diagnost Grp Co Ltd, AI Middle Platform Dept, Guangzhou 510005, Peoples R China

3.South China Agr Univ, Coll Math & Informat, Coll Software Engn, Guangzhou 510642, Peoples R China

4.Guangdong Acad Agr Sci, Inst Facil Agr, Guangzhou 510640, Peoples R China

5.South China Agr Univ, Coll Elect Engn, Guangzhou 510642, Peoples R China

关键词： social relationships; behavioral patterns; stress behavior recognition; multi-object tracking; hierarchical matching mechanism

期刊名称：VETERINARY SCIENCES （ 影响因子：2.3； 五年影响因子：2.4 ）

ISSN：

年卷期： 2025 年 12 卷 7 期

页码：

收录情况： SCI

摘要： Understanding how piglets move around sows during posture changes is crucial for their safety and healthy growth. Automated monitoring can reduce farm labor and help prevent accidents like piglet crushing. Current methods (called Joint Detection-and-Tracking-based, abbreviated as JDT-based) struggle with problems like misidentifying piglets or losing track of them due to crowding, occlusion, and shape changes. To solve this, we developed MSHMTracker, a smarter tracking system that introduces a motion-status hierarchical architecture to significantly improve tracking performance by adapting to piglets' motion statuses. In MSHMTracker, a score- and time-driven hierarchical matching mechanism (STHM) was used to establish the spatio-temporal association by the motion status, helping maintain accurate tracking even in challenging conditions. Finally, piglet group aggregation or dispersion behaviors in response to sow posture changes were identified based on the tracked trajectory information. Tested on 100 videos (30,000+ images), our method achieved 93.8% tracking accuracy (MOTA) and 92.9% identity consistency (IDF1). It outperformed six popular tracking systems (e.g., DeepSort, FairMot). The mean accuracy of behavior recognition was 87.5%. In addition, the correlations (0.6 and 0.82) between piglet stress responses and sow posture changes were explored. This research showed that piglet movements are closely related to sow behavior, offering insights into sow-piglet relationships. This work has the potential to reduce farmers' labor and improve the productivity of animal husbandry.

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