Drought Stress Classification Using 3D Plant Models
Siddharth Srivastava,Swati Bhugra,Brejesh Lall,Santanu Chaudhury +3 more
- pp 2046-2054
TLDR
This paper proposes a novel end-to-end pipeline including 3D reconstruction, segmentation and feature extraction, leveraging deep neural networks at various stages, for drought stress study, and shows that the network outperforms conventional methods.Abstract:
Quantification of physiological changes in plants can capture different drought mechanisms and assist in selection of tolerant varieties in a high throughput manner. In this context, an accurate 3D model of plant canopy provides a reliable representation for drought stress characterization in contrast to using 2D images. In this paper, we propose a novel end-to-end pipeline including 3D reconstruction, segmentation and feature extraction, leveraging deep neural networks at various stages, for drought stress study. To overcome the high degree of self-similarities and self-occlusions in plant canopy, prior knowledge of leaf shape based on features from deep siamese network are used to construct an accurate 3D model using structure from motion on wheat plants. The drought stress is characterized with a deep network based feature aggregation. We compare the proposed methodology on several descriptors, and show that the network outperforms conventional methods.read more
Citations
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Leveraging Image Analysis for High-Throughput Plant Phenotyping
TL;DR: A framework for plant phenotyping in a multimodal, multi-view, time-lapsed, high-throughput imaging system and a taxonomy of phenotypes that may be derived by image analysis for better understanding of morphological structure and functional processes in plants are provided.
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DeepPoint3D: Learning discriminative local descriptors using deep metric learning on 3D point clouds
TL;DR: This paper proposes to learn 3D local descriptors by directly processing unstructured 3D point clouds without needing any intermediate representation, and uses a multi-margin contrastive loss which discriminates between similar and dissimilar points on a surface while also leveraging the extent of dissimilarity among the negative samples at the time of training.
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Implementation of an algorithm for automated phenotyping through plant 3D-modeling: A practical application on the early detection of water stress
Riccardo Rossi,S. Costafreda-Aumedes,Luisa Leolini,Claudio Leolini,Marco Bindi,Marco Moriondo +5 more
TL;DR: In this article , a Structure from Motion (SfM) based segmentation algorithm was proposed for the automatic collection of plant structural parameters based on three-dimensional (3D)-modeling obtained through a phenotyping platform.
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High-throughput field crop phenotyping: current status and challenges
TL;DR: An overview of recent HTP technologies is provided, focusing mainly on canopy-based phenotypes of major crops, such as canopy height, canopy coverage, canopy biomass, and canopy stressed appearance, in addition to crop organ detection and counting in the fields.
Proceedings ArticleDOI
Performance Evalution of 3D Keypoint Detectors and Descriptors for Plants Health Classification
TL;DR: In this paper, the performance of different keypoint detectors and local feature descriptors combinations for the plant growth stage and it's growth condition classification based on 3D point clouds of the plants was compared.
References
More filters
Proceedings ArticleDOI
Object recognition from local scale-invariant features
TL;DR: Experimental results show that robust object recognition can be achieved in cluttered partially occluded images with a computation time of under 2 seconds.
Book ChapterDOI
SURF: speeded up robust features
TL;DR: A novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust Features), which approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster.
Proceedings Article
Visual categorization with bags of keypoints
TL;DR: This bag of keypoints method is based on vector quantization of affine invariant descriptors of image patches and shows that it is simple, computationally efficient and intrinsically invariant.
Journal ArticleDOI
Photo tourism: exploring photo collections in 3D
TL;DR: This work presents a system for interactively browsing and exploring large unstructured collections of photographs of a scene using a novel 3D interface that consists of an image-based modeling front end that automatically computes the viewpoint of each photograph and a sparse 3D model of the scene and image to model correspondences.
Proceedings ArticleDOI
Fast Point Feature Histograms (FPFH) for 3D registration
TL;DR: This paper modifications their mathematical expressions and performs a rigorous analysis on their robustness and complexity for the problem of 3D registration for overlapping point cloud views, and proposes an algorithm for the online computation of FPFH features for realtime applications.