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bioRxiv · 10.1101/2023.08.04.552010

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

Omotara, G.·Tousi, S. M. A.·Decker, J. E.·Brake, D.·DeSouza, G. N.
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Abstract

We introduce a high throughput 3D scanning solution specifically designed to precisely measure cattle phenotypes. This scanner leverages an array of depth sensors, i.e. time-of-flight (Tof) sensors, each governed by dedicated embedded devices. The system excels at generating high-fidelity 3D point clouds, thus facilitating an accurate mesh that faithfully reconstructs the cattle geometry on the fly. In order to evaluate the performance of our system, we have implemented a two-fold validation process. Initially, we test the scanners competency in determining volume and surface area measurements within a controlled environment featuring known objects. Secondly, we explore the impact and necessity of multi-device synchronization when operating a series of time-of-flight sensors. Based on the experimental results, the proposed system is capable of producing high-quality meshes of untamed cattle for livestock studies.

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Omotara, G., Tousi, S. M. A., Decker, J. E., Brake, D., DeSouza, G. N.. 2023-08-09. High-Throughput and Accurate 3D Scanning of Cattle Using Time-of-Flight Sensors and Deep Learning. https://doi.org/10.1101/2023.08.04.552010

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