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Title: 3D Reconstruction-Based Seed Counting of Sorghum Panicles for Agricultural Inspection
In this paper, we present a method for creating high-quality 3D models of sorghum panicles for phenotyping in breeding experiments. This is achieved with a novel reconstruc- tion approach that uses seeds as semantic landmarks in both 2D and 3D. To evaluate the performance, we develop a new metric for assessing the quality of reconstructed point clouds without ground-truth. Finally, a counting method is presented where the density of seed centers in the 3D model allows 2D counts from multiple views to be effectively combined into a whole-panicle count. We demonstrate that using this method to estimate seed count and weight for sorghum outperforms count extrapolation from 2D images, an approach used in most state of the art methods for seeds and grains of comparable size.  more » « less
Award ID(s):
1956163
NSF-PAR ID:
10472716
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
IEEE
Date Published:
Journal Name:
Proceedings IEEE International Conference on Robotics and Automation
ISSN:
1050-4729
Page Range / eLocation ID:
9594 to 9600
Format(s):
Medium: X
Location:
London, United Kingdom
Sponsoring Org:
National Science Foundation
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