@inproceedings{ca35803902df4095beb98a05f64f8775,
title = "Fusion of Low-Density LiDAR Data with RGB Images for Plant 3D Modeling",
abstract = "Plant architecture is defined as the three-dimensional modeling of the plant's morphology for extracting relevant phenological traits. Most applications rely on expensive high-density LiDAR devices for enabling high-throughput mapping. In this paper, we explore the use of low-cost LiDAR equipment by using a sensor fusion approach. The proposed method is based on the fusion of LiDAR-acquired low resolution 3D point cloud data with high resolution 2D imagery. We use an extrinsic calibration method that requires oversampling to enhance the data fusion from both sensors. As a result, we increased the resolution of the output 3D model of the plant.",
keywords = "LiDAR, RGB imagery, plant architecture, plant phenotyping, sensor fusion",
author = "Garcia, {Manuel F.} and Diego Mendez and Colorado, {Julian D.}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 Virtual Symposium in Plant Omics Sciences, OMICAS 2020 ; Conference date: 23-11-2020 Through 27-11-2020",
year = "2020",
month = nov,
day = "23",
doi = "10.1109/OMICAS52284.2020.9535650",
language = "English",
series = "2020 Virtual Symposium in Plant Omics Sciences, OMICAS 2020 - Conference Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Julian Colorado",
booktitle = "2020 Virtual Symposium in Plant Omics Sciences, OMICAS 2020 - Conference Proceedings",
address = "United States",
}