Moo-ving Beyond Tradition: Revolutionizing Cattle Behavioural Phenotyping with Pose Estimation Techniques

TL;DR

This paper reviews recent advancements in pose estimation techniques for cattle, highlighting their potential to improve health monitoring, behavioral analysis, and welfare in the cattle industry, and proposes a collaborative open science platform.

Contribution

It provides a comprehensive review of pose estimation methods for cattle and introduces a platform to foster industry-academia collaboration.

Findings

Pose estimation enables precise cattle movement analysis.

Current methods face challenges in scalability and accuracy.

A new open science platform is proposed to advance research.

Abstract

The cattle industry has been a major contributor to the economy of many countries, including the US and Canada. The integration of Artificial Intelligence (AI) has revolutionized this sector, mirroring its transformative impact across all industries by enabling scalable and automated monitoring and intervention practices. AI has also introduced tools and methods that automate many tasks previously performed by human labor with the help of computer vision, including health inspections. Among these methods, pose estimation has a special place; pose estimation is the process of finding the position of joints in an image of animals. Analyzing the pose of animal subjects enables precise identification and tracking of the animal's movement and the movements of its body parts. By summarizing the video and imagery data into movement and joint location using pose estimation and then analyzing this information, we can address the scalability challenge in cattle management, focusing on health monitoring, behavioural phenotyping and welfare concerns. Our study reviews recent advancements in pose estimation methodologies, their applicability in improving the cattle industry, existing challenges, and gaps in this field. Furthermore, we propose an initiative to enhance open science frameworks within this field of study by launching a platform designed to connect industry and academia.