Paper Info
Title
Plant Volume Estimation Based on Multi-View Stereo and Piecewise Segmentation for Precision Agriculture.
Abstract
Piecewise segmentation approaches of plant volume estimation methods are presented. The primary 3-D reference shape of a target plant is obtained through the 3-D point cloud generation using multi-view stereo techniques. Then, the entire shape region is segmented into multiple pieces to calculate the plant volume. Two different segmentation method of i) slice-based and ii) cell-based are adopted. In the slice-based model, the entire point cloud is horizontally split into slices, whereas in the cell-based model, it is divided into small cubical cells. After that, volume estimation procedures for the two models are applied. Various experiments were performed to test validity of presented methods. Experiments to find the proper number of segments for the methods were also performed.
Year
DOI
Venue
2018
10.3233/978-1-61499-874-7-107
INTELLIGENT ENVIRONMENTS 2018
Keywords
Field
DocType
Plant Volume Estimation,Multi-View Stereo,Precision Agriculture
Computer vision,Segmentation,Computer science,Precision agriculture,Volume estimation,Artificial intelligence,Piecewise
Conference
Volume
ISSN
Citations 
23
1875-4163
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Seong-Hun Lee100.34
Jaehwa Park2659.50