scholarly journals Three Dimensional Reconstruction of Botanical Trees with Simulatable Geometry

2021 ◽  
Vol 4 (3) ◽  
pp. 1-16
Author(s):  
Ed Quigley ◽  
Winnie Lin ◽  
Yilin Zhu ◽  
Ronald Fedkiw
Keyword(s):  
Physical Simulation ◽  
State Of The Art ◽  
Three Dimensional ◽  
Image Data ◽  
Point Clouds ◽  
Future Research ◽  
Geometric Accuracy ◽  
Rigid Body Model ◽  
Dimensional Reconstruction ◽  
Pros And Cons

We tackle the challenging problem of creating full and accurate three dimensional reconstructions of botanical trees with the topological and geometric accuracy required for subsequent physical simulation, e.g. in response to wind forces. Although certain aspects of our approach would benefit from various improvements, our results exceed the state of the art especially in geometric and topological complexity and accuracy. Starting with two dimensional RGB image data acquired from cameras attached to drones, we create point clouds, textured triangle meshes, and a simulatable and skinned cylindrical articulated rigid body model. We discuss the pros and cons of each step of our pipeline, and in order to stimulate future research we make the raw and processed data from every step of the pipeline as well as the final geometric reconstructions publicly available.

Three-dimensional reconstruction of metabolic data from quantitative autoradiography of rat brain

1984 ◽  
Vol 247 (3) ◽  
pp. E412-E419 ◽  
Author(s):  
L. S. Hibbard ◽  
R. A. Hawkins
Keyword(s):  
High Speed ◽  
Three Dimensional ◽  
Image Data ◽  
Brain Structures ◽  
Three Dimensions ◽  
Quantitative Autoradiography ◽  
Alignment Algorithm ◽  
Computer Methods ◽  
Mathematical Properties ◽  
Dimensional Reconstruction

Quantitative autoradiography is a powerful method for studying brain function by the determination of blood flow, glucose utilization, or transport of essential nutrients. Autoradiographic images contain vast amounts of potentially useful information, but conventional analyses can practically sample the data at only a small number of points arbitrarily chosen by the experimenter to represent discrete brain structures. To use image data more fully, computer methods for its acquisition, storage, quantitative analysis, and display are required. We have developed a system of computer programs that performs these tasks and has the following features: 1) editing and analysis of single images using interactive graphics, 2) an automatic image alignment algorithm that places images in register with one another using only the mathematical properties of the images themselves, 3) the calculation of mean images from equivalent images in different experimental serial image sets, 4) the calculation of difference images (e.g., experiment-minus-control) with the option to display only differences estimated to be statistically significant, and 5) the display of serial image metabolic maps reconstructed in three dimensions using a high-speed computer graphics system.

scholarly journals Toward a Novel Laser-Based Approach for Estimating Snow Interception

2020 ◽  
Vol 12 (7) ◽  
pp. 1146 ◽  
Author(s):  
Micah Russell ◽  
Jan U. H. Eitel ◽  
Andrew J. Maguire ◽  
Timothy E. Link
Keyword(s):  
Laser Scanning ◽  
Three Dimensional ◽  
Point Clouds ◽  
Primary Objective ◽  
Snow Accumulation ◽  
Future Research ◽  
Snow Density ◽  
Canopy Interception ◽  
Terrestrial Lidar ◽  
Large Trees

Forests reduce snow accumulation on the ground through canopy interception and subsequent evaporative losses. To understand snow interception and associated hydrological processes, studies have typically relied on resource-intensive point scale measurements derived from weighed trees or indirect measurements that compared snow accumulation between forested sites and nearby clearings. Weighed trees are limited to small or medium-sized trees, and indirect comparisons can be confounded by wind redistribution of snow, branch unloading, and clearing size. A potential alternative method could use terrestrial lidar (light detection and ranging) because three-dimensional lidar point clouds can be generated for any size tree and can be utilized to calculate volume of the intercepted snow. The primary objective of this study was to provide a feasibility assessment for estimating snow interception volume with terrestrial laser scanning (TLS), providing information on challenges and opportunities for future research. During the winters of 2017 and 2018, intercepted snow masses were continuously measured for two model trees suspended from load-cells. Simultaneously, autonomous terrestrial lidar scanning (ATLS) was used to develop volumetric estimates of intercepted snow. Multiplying ATLS volume estimates by snow density estimates (derived from empirical models based on air temperature) enabled the comparison of predicted vs. measured snow mass. Results indicate agreement between predicted and measured values (R2 ≥ 0.69, RMSE ≥ 0.91 kg, slope ≥ 0.97, intercept ≥ −1.39) when multiplying TLS snow interception volume with a constant snow density estimate. These results suggest that TLS might be a viable alternative to traditional approaches for mapping snow interception, potentially useful for estimating snow loads on large trees, collecting data in difficult to access terrain, and calibrating snow interception models to new forest types around the globe.

Kinect Depth Data Segmentation Based on Gauss Mixture Model Clustering

2013 ◽  
Vol 760-762 ◽  
pp. 1556-1561
Author(s):  
Ting Wei Du ◽  
Bo Liu
Keyword(s):  
Mixture Model ◽  
Point Cloud ◽  
Three Dimensional ◽  
Image Data ◽  
Point Clouds ◽  
Gaussian Mixture ◽  
Depth Image ◽  
Cloud Data ◽  
Mixture Model Clustering ◽  
Gauss Mixture

Indoor scene understanding based on the depth image data is a cutting-edge issue in the field of three-dimensional computer vision. Taking the layout characteristics of the indoor scenes and more plane features in these scenes into account, this paper presents a depth image segmentation method based on Gauss Mixture Model clustering. First, transform the Kinect depth image data into point cloud which is in the form of discrete three-dimensional point data, and denoise and down-sample the point cloud data; second, calculate the point normal of all points in the entire point cloud, then cluster the entire normal using Gaussian Mixture Model, and finally implement the entire point clouds segmentation by RANSAC algorithm. Experimental results show that the divided regions have obvious boundaries and segmentation quality is above normal, and lay a good foundation for object recognition.

scholarly journals Approaches to three-dimensional reconstruction of plant shoot topology and geometry

2017 ◽  
Vol 44 (1) ◽  
pp. 62 ◽  
Author(s):  
Jonathon A. Gibbs ◽  
Michael Pound ◽  
Andrew P. French ◽  
Darren M. Wells ◽  
Erik Murchie ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Image Data ◽  
3D Models ◽  
Crop Productivity ◽  
Automated System ◽  
Dimensional Reconstruction ◽  
Climate Adaption ◽  
Accuracy And Repeatability ◽  
Plant Shoots ◽  
Severe Flooding

There are currently 805 million people classified as chronically undernourished, and yet the World’s population is still increasing. At the same time, global warming is causing more frequent and severe flooding and drought, thus destroying crops and reducing the amount of land available for agriculture. Recent studies show that without crop climate adaption, crop productivity will deteriorate. With access to 3D models of real plants it is possible to acquire detailed morphological and gross developmental data that can be used to study their ecophysiology, leading to an increase in crop yield and stability across hostile and changing environments. Here we review approaches to the reconstruction of 3D models of plant shoots from image data, consider current applications in plant and crop science, and identify remaining challenges. We conclude that although phenotyping is receiving an increasing amount of attention – particularly from computer vision researchers – and numerous vision approaches have been proposed, it still remains a highly interactive process. An automated system capable of producing 3D models of plants would significantly aid phenotyping practice, increasing accuracy and repeatability of measurements.

scholarly journals Visual Three-Dimensional Reconstruction of Aortic Dissection Based on Medical CT Images

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Xiaojie Duan ◽  
Dandan Chen ◽  
Jianming Wang ◽  
Meichen Shi ◽  
Qingliang Chen ◽  
...  
Keyword(s):  
Aortic Dissection ◽  
Rapid Development ◽  
Hessian Matrix ◽  
Three Dimensional ◽  
Image Data ◽  
Ray Casting ◽  
Initial Shape ◽  
Spatial Continuity ◽  
Training Samples ◽  
Dimensional Reconstruction

With the rapid development of CT technology, especially the higher resolution of CT machine and a sharp increase in the amount of slices, to extract and three-dimensionally display aortic dissection from the huge medical image data became a challenging task. In this paper, active shape model combined with spatial continuity was adopted to realize automatic reconstruction of aortic dissection. First, we marked aortic feature points from big data sample library and registered training samples to build a statistical model. Meanwhile, gray vectors were sampled by utilizing square matrix, which set the landmarks as the center. Posture parameters of the initial shape were automatically adjusted by the method of spatial continuity between CT sequences. The contrast experiment proved that the proposed algorithm could realize accurate aorta segmentation without selecting the interested region, and it had higher accuracy than GVF snake algorithm (93.29% versus 87.54% on aortic arch, 94.30% versus 89.25% on descending aorta). Aortic dissection membrane was extracted via Hessian matrix and Bayesian theory. Finally, the three-dimensional visualization of the aortic dissection was completed by volume rendering based on the ray casting method to assist the doctors in clinical diagnosis, which contributed to improving the success rate of the operations.

scholarly journals Métodos de Interpolación Basados en Funciones de Base Radial con Aplicaciones a la Reconstrucción de Imágenes

2018 ◽  
Vol 3 (1) ◽  
pp. 563
Author(s):  
Rodrigo Combe ◽  
Idulfo Arrocha
Keyword(s):  
Surface Reconstruction ◽  
Interpolation Method ◽  
Three Dimensional ◽  
Point Clouds ◽  
Implicit Surface ◽  
Implicit Functions ◽  
Interpolation Methods ◽  
Three Dimensional Objects ◽  
Dimensional Reconstruction ◽  
Base Functions

This article presents the Radial Base Functions (RBFs) as a functional interpolation method for implicit surface reconstruction from points cloud.  These methods allow not only to improve inaccuracies resulting from scanners, but also possible discontinuities that occur in the point clouds.  The complexity of three-dimensional objects makes reconstruction difficult since devices such as scanners do not always faithfully reproduce the objects, which can lead to information gaps or an incomplete reconstruction. Interpolation methods based on RBFs allow to correct these errors.  Three-dimensional surface reconstruction has wide applications in biomedical engineering, in the design of industrial parts, among others.  With the algorithm, we developed we have been able to make reconstructions of both explicit and implicit functions, in two and three dimensions.Keywords:  Radial Basis Functions, Three-dimensional reconstruction, Interpolation Methods.

scholarly journals 3D SURFACE RECONSTRUCTION FROM MULTI-DATE SATELLITE IMAGES

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 313-320
Author(s):  
S. Bullinger ◽  
C. Bodensteiner ◽  
M. Arens
Keyword(s):  
Large Scale ◽  
Satellite Images ◽  
Stereo Matching ◽  
State Of The Art ◽  
Satellite Image ◽  
Three Dimensional ◽  
Point Clouds ◽  
Reconstruction Algorithms ◽  
Depth Maps ◽  
Median Error

Abstract. The reconstruction of accurate three-dimensional environment models is one of the most fundamental goals in the field of photogrammetry. Since satellite images provide suitable properties for obtaining large-scale environment reconstructions, there exist a variety of Stereo Matching based methods to reconstruct point clouds for satellite image pairs. Recently, a Structure from Motion (SfM) based approach has been proposed, which allows to reconstruct point clouds from multiple satellite images. In this work, we propose an extension of this SfM based pipeline that allows us to reconstruct not only point clouds but watertight meshes including texture information. We provide a detailed description of several steps that are mandatory to exploit state-of-the-art mesh reconstruction algorithms in the context of satellite imagery. This includes a decomposition of finite projective camera calibration matrices, a skew correction of corresponding depth maps and input images as well as the recovery of real-world depth maps from reparameterized depth values. The paper presents an extensive quantitative evaluation on multi-date satellite images demonstrating that the proposed pipeline combined with current meshing algorithms outperforms state-of-the-art point cloud reconstruction algorithms in terms of completeness and median error. We make the source code of our pipeline publicly available.

scholarly journals Energy Management for Smart Homes—State of the Art

2019 ◽  
Vol 9 (17) ◽  
pp. 3459 ◽  
Author(s):  
Lashkari ◽  
Chen ◽  
Musilek
Keyword(s):  
Smart Home ◽  
State Of The Art ◽  
Smart Homes ◽  
Future Research ◽  
Context Aware ◽  
Future Perspectives ◽  
Research Directions ◽  
Pros And Cons ◽  
Future Research Directions ◽  
Household Activities

Smart home is a concept that aims to enhance the comfort of residents and facilitate household activities. The smart home is an application of ubiquitous computing which can provide the user with context-aware automated or assistive services in the form of ambient intelligence, remote control of home appliances, or automation. Smart homes attempt to integrate smartness into homes to guarantee the residents’ convenience, safety, and security, while conserving the energy. The capabilities of a smart home in the context of different applications, have been scrutinized for this investigation. Different proposed architectures, protocols, and infrastructures have been taken into consideration. As the data management process is a vital part of a smart home system, many procedures of data collection, storage, and analysis have been surveyed. Methods of data acquisition has also been discussed. Existing challenges, pros, and cons of proposed schemes along with future perspectives of smart homes are identified in this report, which is intended to promote future research directions.

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