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Feature Extraction and Automatic Recognition Model Construction for Head Back Posture During the Parturition Process

Xia Li1,2,3, Yifeng Song1,2,3, Xiaoping An1,2,3

  • 1College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.

Animals : an Open Access Journal From MDPI
|September 13, 2025
PubMed
Summary

Computer vision accurately detects the "head back" posture during cow calving, aiding timely intervention. This technology enhances animal welfare by monitoring labor and identifying high-risk births in primiparous cows.

Keywords:
YOLOv8computer visiondairy cowsparturition process

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Area of Science:

  • Veterinary Science
  • Animal Behavior
  • Computer Vision

Background:

  • The 'head back' posture during bovine parturition is a key indicator of pain and labor.
  • Real-time monitoring of calving behaviors can improve animal welfare and facilitate timely assistance.

Purpose of the Study:

  • To develop and evaluate a computer vision model for recognizing head posture during parturition.
  • To analyze behavioral differences in primiparous versus multiparous cows during calving.

Main Methods:

  • Utilized the YOLOv8 algorithm trained on 25,617 images to classify cow postures.
  • Assessed model performance across various camera angles and environmental conditions (lighting, time of day).
  • Conducted behavioral analysis comparing primiparous and multiparous cows.

Main Results:

  • The YOLOv8 model achieved a 0.71 F1 score for posture recognition.
  • Posture recognition accuracy exceeded 90% from abdominal camera angles and remained stable under diverse lighting.
  • Primiparous cows showed significantly longer parturition durations and head back posture durations.

Conclusions:

  • Computer vision offers a promising tool for real-time monitoring of bovine parturition.
  • The developed model can aid in identifying calving difficulties and enhancing animal welfare.
  • Significant behavioral differences exist between primiparous and multiparous cows during calving.