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High-Throughput and Accurate 3D Scanning of Cattle Using Time-of-Flight Sensors and Deep Learning.

Gbenga Omotara¹, Seyed Mohamad Ali Tousi¹, Jared Decker²

¹Vision-Guided and Intelligent Robotics Laboratory, Electrical Engineering and Computer Science Department, University of Missouri, Columbia, MO 65201, USA.

Sensors (Basel, Switzerland)

|August 29, 2024

Summary

A new high-throughput 3D scanning system accurately measures cattle phenotypes using time-of-flight (ToF) sensors and deep learning. This technology provides precise volume and surface area measurements for livestock studies.

Keywords:

3D surface reconstruction cattle scanner deep learning segmentation

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Area of Science:

Agricultural Engineering
Computer Vision
Animal Science

Background:

Accurate phenotyping is crucial for livestock management and genetic improvement.
Existing methods for cattle phenotyping can be time-consuming and lack precision.

Purpose of the Study:

To develop and validate a high-throughput 3D scanning system for accurate cattle phenotype measurement.
To assess the system's performance in reconstructing cattle geometry and calculating volume and surface area.

Main Methods:

Utilized an array of time-of-flight (ToF) depth sensors controlled by embedded devices.
Implemented a deep learning approach for automatic stitching of 3D point clouds using combined RGB and depth data.
Conducted a two-fold validation: controlled environment with known objects and real-world measurements on cattle.

Main Results:

The system generates high-fidelity 3D point clouds and accurate meshes of cattle geometry.
Quantitative validation confirmed precise volume and surface area measurements in controlled and real-world settings.
Demonstrated the system's capability to handle moving targets and produce high-quality reconstructions of untamed cattle.

Conclusions:

The developed 3D scanning system offers a non-invasive, accurate, and high-throughput solution for cattle phenotyping.
This technology has significant potential to advance livestock research and breeding programs.
The system's ability to provide precise measurements supports data-driven decision-making in animal agriculture.