在视频上追踪个体肉的时间和距离
J E Doornweerd1, R F Veerkamp1, B de Klerk2
1Animal Breeding and Genomics, Wageningen University & Research, 6700 AH Wageningen, the Netherlands.
Poultry science
|November 19, 2023
概括
使用视频帮助追踪个体 brojlers 的遗传改进,但相似的外观带来了挑战. 这项研究分析了跟踪错误,确定饮酒者遮蔽和近距离作为未来表型改进的关键问题.
科学领域:
- 动物科学 动物科学
- 农业工程 农业工程
- 计算机视觉 计算机视觉
背景情况:
- 通过视频进行个别肉追踪,可以了解基因改进的健康,福利和性能.
- 在群体环境中出现类似的肉,会给跟踪带来重大挑战.
研究的目的:
- 在视频上分析肉追踪性能,包括ID开关,追踪时间和距离.
- 检查跟踪错误,如与位置,近距离和动力学相关的ID丢失.
- 为了建立一个基线,用于肉的运动表型在集体住房设置.
主要方法:
- 采用YOLOv7微型模型来检测肉,在测试套件上达到高精度 (0.99).
- 实施了一个SORT多对象追踪器,根据13只白肉的地面真实轨迹进行评估.
- 分析了136分钟的视频数据,来自18天大的肉在实验笔中.
主要成果:
- 追踪错误主要与饮酒者和近距离 (在10厘米以内) 的肉封闭有关.
- 与空间因素相比,速度和加速对跟踪错误的影响较小.
- 识别开关平均每轨迹9.92,跟踪时间和距离差异很大.
结论:
- 群体养肉的视频跟踪对运动表型有潜力,但面临像ID开关这样的挑战.
- 在跟踪算法中解决阻塞和接近问题对于提高准确性至关重要.
- 建议使用外部动物识别系统来实现客观,同时和半连续的表型.
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