OpenAcces_RGBD_apple_dataset

Intel realsense d435i open access dataset of seasonal growth of fuji apple. The dataset contains images and reference caliper ground truth data. Data were collected during 2022 season in a 3 years old apple orchard trained as 'Planar Cordon' (bidimensional training system). 12 fruit on two trees (24 fruit in total) were monitored for their fruit size along the whole season. RGB-D pictures, manually labelled for the monitored fruit, were taken on 17 different dates from a fruit size of 40mm approx. to >80mm approx For more detailed info check the 'data_exploration' Jupyter notebook in the notebook folder Other information regarding the dataset and results obtained with that can be found in the following papers: 67 Apple fruit sizing through low-cost depth camera and neural network application - https://doi.org/10.3920/978-90-8686-947-3_67 A Computer Vision Approach for Estimating Fruit Growth Rate in Orchards - IN PRESS in Acta Horticulturae as conference proceedings of ISHS PMOV conference英特尔实感（Intel RealSense）D435i 富士苹果季节生长开放获取数据集。本数据集包含图像与基于游标卡尺的基准真值（ground truth）数据。数据采集于2022年生长季，采集自树龄3年、采用「平面棚架（Planar Cordon，即二维整形体系）」的苹果园。选取两棵树上的12个果实（总计24个），在整个生长季内对其果径大小进行持续监测。在果径约40毫米至大于80毫米的阶段内，分17个不同日期采集了针对监测果实进行人工标注的RGB-D（彩色-深度）图像。如需获取更详细的信息，请查看notebooks文件夹中的"data_exploration" Jupyter记事本（Jupyter notebook）。有关本数据集的其他信息及基于该数据集得到的研究成果可参阅以下论文：1. 《基于低成本深度相机与神经网络应用的苹果果实尺寸估算》（67 Apple fruit sizing through low-cost depth camera and neural network application）——DOI: 10.3920/978-90-8686-947-3_67；2. 《果园果实生长速率估算的计算机视觉方法》（A Computer Vision Approach for Estimating Fruit Growth Rate in Orchards）——已被《园艺学学报（Acta Horticulturae）》接收，作为国际园艺学会（ISHS）PMOV会议的会议论文集内容。

搜集汇总

背景与挑战

背景概述

该数据集是一个开放访问的RGB-D苹果数据集，专注于富士苹果在季节性生长过程中的监测。它包含2022年季节在苹果园中采集的图像和卡尺测量真实数据，覆盖24个苹果从约40毫米到超过80毫米的17个不同时间点的生长数据，适用于计算机视觉和农业研究应用。