Estimation of pig body measurements based on keypoint detection and multi-object tracking

YAO Yipeng; XU Chen; CHEN Hongji; LIU Yong; XU Shunlai

doi:10.7671/j.issn.1001-411X.202404012

Journal of South China Agricultural University > 2024 > 45(5): 722-729. > DOI: 10.7671/j.issn.1001-411X.202404012

YAO Yipeng, XU Chen, CHEN Hongji, et al. Estimation of pig body measurements based on keypoint detection and multi-object tracking[J]. Journal of South China Agricultural University, 2024, 45(5): 722-729. DOI: 10.7671/j.issn.1001-411X.202404012

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Estimation of pig body measurements based on keypoint detection and multi-object tracking

YAO Yipeng^{1, 2,},
XU Chen^{1, 2},
CHEN Hongji²,
LIU Yong²,
XU Shunlai^2, ,

1.
College of Computer and Information Science/College of Software, Southwest University, Chongqing 400700, China
2.
Chongqing Academy of Animal Science/National Center of Technology Innovation for Pigs, Chongqing 402460, China

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Received Date: April 05, 2024
Available Online: June 23, 2024
Published Date: June 30, 2024

Graphical Abstract

Abstract

Abstract

Objective
To reduce the manual workload of measuring pig body measurements in pig farms and improve measurement accuracy and efficiency.
Method
An automatic pig body measurement estimation method based on keypoint detection and multi-object tracking was proposed. The method utilized Yolov8-Pose model to identify keypoints and bounding boxes of individual pigs. ByteTrack algorithm was employed for real-time tracking of the pig herd. Regions of interest were introduced to mitigate image distortion and improve recognition speed. Additionally, a posture and anomaly detection filter algorithm was designed to reduce errors caused by motion blur, posture abnormality and other factors.
Result
The mean absolute errors of the body length, shoulder width, and hip width of 24 pigs in five pigpens were less than 3 cm, the mean absolute percentage errors were maintained below 4%, 6% and 7% respectively. The data processing speed reached 19.3 frames/s.
Conclusion
The proposed method for pig body measurement estimation based on keypoint detection and multi-object tracking provides a lightweight and easily deployable solution for automatic body measurement in pig farming scenarios.
- Yolov8-Pose,
- Region of interest,
- Body measurement estimation,
- Keypoint,
- Target detection box,
- Pig

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References (21)

References

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