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A Novel Single Animal Motor Function Tracking System Using Simple, Readily Available Software

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Quick, Accurate, Smart: 3D Computer Vision Technology Helps Assessing Confined Animals' Behaviour.

Shanis Barnard¹, Simone Calderara², Simone Pistocchi²

¹Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise, Teramo, Italy.

|July 15, 2016

Summary

This study introduces novel software using 3D vision and machine learning to automatically analyze dog behavior in kennels. This technology objectively assesses animal welfare by recognizing movement patterns, reducing human subjectivity and time constraints.

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Area of Science:

Animal behavior science
Computer vision
Machine learning

Background:

Domestic animals' welfare is often inferred from behavior, but manual observation is time-consuming and subjective.
Current methods for assessing animal welfare through behavior analysis lack objectivity and efficiency.

Purpose of the Study:

To develop and validate a prototype software for automatic animal behavior recognition using 3D visual data.
To objectively assess the quality of life for animals in artificial housing by analyzing behavioral indicators.

Main Methods:

Utilized 3D visual data, body part detection, and machine learning frameworks for behavior inference.
Developed software capable of clustering temporal movement patterns without a pre-set ethogram.
Incorporated a validation process to check the software's accuracy in detecting dog behavior.

Main Results:

The software successfully inferred dog behavior from 3D visual data, identifying postures and movement patterns.
Demonstrated the ability to cluster movement patterns automatically and assess deviations from normal behavior.
Achieved accuracy in behavior detection through a validation process, independent of human subjectivity.

Conclusions:

An automated behavior recognition system using 3D computer vision offers an objective and efficient method for assessing animal welfare in confinement.
The developed 3D framework is adaptable to various quadruped species in artificial housing and represents an innovative approach in animal behavior science.
Further research and validation are necessary, but the system shows potential for significant advancements in animal welfare studies.