Spot centroid extraction algorithm based on three-dimensional arctangent function fitting

2019 ◽  
Vol 48 (2) ◽  
pp. 226001 ◽  
Author(s):  
张 惠 Zhang Hui ◽  
李国平 Li Guoping ◽  
张 勇 Zhang Yong ◽  
胡守伟 Hu Shouwei
Keyword(s):  
Three Dimensional ◽  
Function Fitting ◽  
Extraction Algorithm ◽  
Arctangent Function

scholarly journals Quadcopter localization and health monitoring method based on multiple virtual silhouette sensor integration

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771771982
Author(s):  
Jie Hou ◽  
Baolong Guo ◽  
Juanjuan Zhu ◽  
Cheng Li ◽  
Wangpeng He
Keyword(s):  
Health Monitoring ◽  
Safety Issue ◽  
Three Dimensional ◽  
General Purpose ◽  
Monitoring Methods ◽  
Monitoring Method ◽  
Extraction Algorithm ◽  
Silhouette Information ◽  
Flight Regimes ◽  
Shadow Projection

With the widespread deployment of quadcopters, the flight safety issue attracts increasingly public and academic attentions. This article presents a quadcopter flight regime extraction algorithm for quadcopter localization and health monitoring using imageries captured by general purpose monocular cameras. First, contour information is extracted from quadcopter shadows on the ground. In order to better illustrate the three-dimensional silhouette information contained in shadow contour on the ground, a virtual sensor named Shadow Projection Tunnel is designed. Then, multiple Shadow Projection Tunnels are generated according to the extracted silhouette information and corresponding light source positions. Finally, three-dimensional quadcopter positions and flight regimes are extracted based on the aggregation between multiple Shadow Projection Tunnels. The proposed method is validated to be accurate and efficient in monitoring quadcopter position and flight regimes based on the comparative analyses. In comparison with traditional quadcopter health monitoring methods, the proposed method has advantages on deployment convenience, system robustness, precision expandability, and scenario adaptability, making it an ideal solution for quadcopter monitoring in outdoor scenarios.

scholarly journals Three-dimensional mechanical parts reconstruction technology based on two-dimensional image

2020 ◽  
Vol 17 (2) ◽  
pp. 172988142091000
Author(s):  
Jiaofei Huo ◽  
Xiaomo Yu
Keyword(s):  
Image Processing ◽  
Stereo Vision ◽  
Stereo Matching ◽  
Vision System ◽  
Three Dimensional ◽  
Three Dimensional Reconstruction ◽  
Stereo Vision System ◽  
Binocular Stereo Vision ◽  
Extraction Algorithm ◽  
Dimensional Reconstruction

With the development of computer technology and three-dimensional reconstruction technology, three-dimensional reconstruction based on visual images has become one of the research hotspots in computer graphics. Three-dimensional reconstruction based on visual image can be divided into three-dimensional reconstruction based on single photo and video. As an indirect three-dimensional modeling technology, this method is widely used in the fields of film and television production, cultural relics restoration, mechanical manufacturing, and medical health. This article studies and designs a stereo vision system based on two-dimensional image modeling technology. The system can be divided into image processing, camera calibration, stereo matching, three-dimensional point reconstruction, and model reconstruction. In the part of image processing, common image processing methods, feature point extraction algorithm, and edge extraction algorithm are studied. On this basis, interactive local corner extraction algorithm and interactive local edge detection algorithm are proposed. It is found that the Harris algorithm can effectively remove the features of less information and easy to generate clustering phenomenon. At the same time, the method of limit constraints is used to match the feature points extracted from the image. This method has high matching accuracy and short time. The experimental research has achieved good matching results. Using the platform of binocular stereo vision system, each step in the process of three-dimensional reconstruction has achieved high accuracy, thus achieving the three-dimensional reconstruction of the target object. Finally, based on the research of three-dimensional reconstruction of mechanical parts and the designed binocular stereo vision system platform, the experimental results of edge detection, camera calibration, stereo matching, and three-dimensional model reconstruction in the process of three-dimensional reconstruction are obtained, and the full text is summarized, analyzed, and prospected.

Very-large-scale motions in a turbulent boundary layer

2011 ◽  
Vol 673 ◽  
pp. 80-120 ◽  
Author(s):  
JAE HWA LEE ◽  
HYUNG JIN SUNG
Keyword(s):  
Boundary Layer ◽  
Shear Stress ◽  
Turbulent Boundary Layer ◽  
Large Scale ◽  
Spatial Organization ◽  
Reynolds Shear Stress ◽  
Three Dimensional ◽  
Hairpin Vortices ◽  
Extraction Algorithm ◽  
Normal Distance

Direct numerical simulation of a turbulent boundary layer was performed to investigate the spatially coherent structures associated with very-large-scale motions (VLSMs). The Reynolds number was varied in the range Reθ = 570–2560. The main simulation was conducted by using a computational box greater than 50δo in the streamwise domain, where δo is the boundary layer thickness at the inlet, and inflow data was obtained from a separate inflow simulation based on Lund's method. Inspection of the three-dimensional instantaneous fields showed that groups of hairpin vortices are coherently arranged in the streamwise direction and that these groups create significantly elongated low- and high-momentum regions with large amounts of Reynolds shear stress. Adjacent packet-type structures combine to form the VLSMs; this formation process is attributed to continuous stretching of the hairpins coupled with lifting-up and backward curling of the vortices. The growth of the spanwise scale of the hairpin packets occurs continuously, so it increases rapidly to double that of the original width of the packets. We employed the modified feature extraction algorithm developed by Ganapathisubramani, Longmire & Marusic (J. Fluid Mech., vol. 478, 2003, p. 35) to identify the properties of the VLSMs of hairpin vortices. In the log layer, patches with the length greater than 3δ–4δ account for more than 40% of all the patches and these VLSMs contribute approximately 45% of the total Reynolds shear stress included in all the patches. The VLSMs have a statistical streamwise coherence of the order of ~6δ; the spatial organization and coherence decrease away from the wall, but the spanwise width increases monotonically with the wall-normal distance. Finally, the application of linear stochastic estimation demonstrated the presence of packet organization in the form of a train of packets in the log layer.

The Trees Skeleton Extraction Based on Point Cloud Contraction

2013 ◽  
Vol 475-476 ◽  
pp. 355-360
Author(s):  
Gui Zhen He
Keyword(s):  
Point Cloud ◽  
Undirected Graph ◽  
Three Dimensional ◽  
Three Dimensional Model ◽  
Extraction Algorithm ◽  
Point Set ◽  
Dimensional Simulation ◽  
Curve Skeleton ◽  
Edge Collapse ◽  
Curve Form

To achieve the trees three dimensional simulation, the most critical step is to extract the trees skeleton. This paper focuses on the point cloud contraction-based skeletal extraction algorithm, uses neighbors to build a transformation matrix, extract a discrete point set approximated to the real skeleton by Laplacian contraction, and constructs a 1D curve skeleton with the help of a weighted undirected graph and edge collapse algorithm. 1D curve form is more easy to operate, guide the reconstruction of three-dimensional model, solve the problem of incomplete data in the process of modeling .

Three Dimensional Point Clouds Watermarking Algorithm Based on Sphere Degenerated Octree

2011 ◽  
Vol 314-316 ◽  
pp. 2064-2070 ◽  
Author(s):  
Jian Xin Liu ◽  
Han Guo Cui ◽  
Xing Dai
Keyword(s):  
Three Dimensional ◽  
Point Clouds ◽  
Component Analysis ◽  
Primary Component ◽  
Experimental Results ◽  
Synchronization Error ◽  
Blind Detection ◽  
Extraction Algorithm ◽  
Uniform Scaling ◽  
Original Point

To ensure the security and integrity of three dimensional point clouds model during transmission in the network, according to their own characteristics, after the pretreatment of PCA (Primary Component Analysis), three dimensional point clouds watermarking embedding algorithm based on sphere degenerated octree was proposed, and the octree that contained the original point clouds model was subdivided multilevel from top to bottom, and the nodes of the octree were ordered. And three dimensional point clouds watermarking extraction algorithm was proposed, and the original point clouds model and the watermarked model were registered accurately, and the occurrence of synchronization error was avoided. Experimental results showed that the presented algorithm was robust to many attacks such as rotation, translation, uniform scaling, vertices reordering, simplifying, noise and cropping under blind detection.

scholarly journals EXPLOITING 3D ULTRASOUND FOR FETAL DIAGNOSTIC PURPOSE THROUGH FACIAL LANDMARKING

2014 ◽  
Vol 33 (3) ◽  
pp. 167 ◽  
Author(s):  
Enrico Vezzetti ◽  
Domenico Speranza ◽  
Federica Marcolin ◽  
Giulia Fracastoro ◽  
Giorgia Buscicchio
Keyword(s):  
State Of The Art ◽  
Three Dimensional ◽  
Aesthetic Surgery ◽  
Point Clouds ◽  
3D Ultrasound ◽  
Diagnostic Purpose ◽  
Expression Recognition ◽  
Principal Curvatures ◽  
Extraction Algorithm ◽  
The Mean

In the last decade, three-dimensional landmarking has gained attention for different applications, such as face recognition for both identification of suspects and authentication, facial expression recognition, corrective and aesthetic surgery, syndrome study and diagnosis. This work focuses on the last one by proposing a geometrically-based landmark extraction algorithm aimed at diagnosing syndromes on babies before their birth. Pivotal role in this activity is the support provided by physicians and 3D ultrasound tools for working on real faces. In particular, the landmarking algorithm here proposed only relies on descriptors coming from Differential Geometry (Gaussian, mean, and principal curvatures, derivatives, coefficients of first and second fundamental forms, Shape and Curvedness indexes) and is tested on nine facial point clouds referred to nine babies taken by a three-dimensional ultrasound tool at different weeks' gestation. The results obtained, validated with the support of four practitioners, show that the localization is quite accurate. All errors lie in the range between 0 and 3.5 mm and the mean distance for each shell is in the range between 0.6 and 1.6 mm. The landmarks showing the highest errors are the ones belonging to the mouth region. Instead, the most precise landmark is the pronasal, on the nose tip, with a mean distance of 0.55 mm. Relying on current literature, this study is something missing in the state-of-the-art of the field, as present facial studies on 3D ultrasound do not work on automatic landmarking yet.

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