Depth distortion correction for consumer-grade depth cameras in crop reconstruction

作     者：Cailian Lao Yu Feng Han Yang 

作者机构：Key Laboratory of Modern Precision Agriculture System Integration ResearchMinistry of EducationChina Agricultural UniversityBeijing 100083PR China Key Laboratory of Agricultural Information Acquisition TechnologyMinistry of Agriculture and Rural AffairsChina Agricultural UniversityBeijing 100083PR China 

出 版 物：《Information Processing in Agriculture》 (农业信息处理（英文）)

年 卷 期：2023年第10卷第4期

页      面：523-534页

核心收录：

学科分类：1304[艺术学-美术学] 13[艺术学] 08[工学] 0804[工学-仪器科学与技术] 0802[工学-机械工程] 

基　　金：supported by the National Natural Science Foundation of China[grant number 31871527] 

主　　题：RGB-D camera Structured light Distortion Depth correction Point cloud 

摘      要：Modern consumer-grade RGB-D cameras provide intensive depth estimation and high frame *** have been widely used in ***,depth anamorphose occurswhen using the RGB-D *** order to address this issue,this paper proposes a novel approach to correct the distorted depth images that fit the relationship between the true distances and the depth values from depth *** study considers the structured light camera ASUS Xtion PRO LIVE as example to develop a system for obtaining a series of depth images at different distances from the target plane.A comparison analysis is conducted between the images before and after correction to evaluate the performance of the distortion *** point cloud image of corrected maize leaves is well coincident with the original *** approach improves the accuracy of depth measurement and optimizes the subsequent use of the depth camera in crop reconstruction and phenotyping studies.