Multi-View 3D Object Reconstruction Using Coordinate Transformation

2013 ◽  
Vol 284-287 ◽  
pp. 2167-2170 ◽  
Author(s):  
Ji Hun Park
Keyword(s):  
Coordinate Transformation ◽  
Digital Camera ◽  
Optimal Solution ◽  
Calibration Method ◽  
Target Object ◽  
Feature Points ◽  
Geometric Information ◽  
Local Coordinates ◽  
Camera Parameters ◽  
Parameter Values

The algorithm presented in this paper takes at least two images taken by an ordinary digital camera, computes camera parameters and outputs scene geometric information. The method takes at least one right-angle triangle in the scene, install a local coordinate at each triangle, and compute camera parameters by using the local coordinate transformation. The algorithm computes orientations and displacement relationships among the triangles in the scene while correcting the previously computed camera parameter values. In order to find optimal solution, we set optimization variables as camera calibration parameters and coordinate transformation values between local coordinates. The background eliminated images and calculated camera parameters allow us to reconstruct a 3D target object in VRML. The merit of this algorithm is in handling varying focal camera, in easy initial guessing value computation and in using fewer feature points compared to Zhang’s calibration method.

A Method on Monocular Vision of Camera for Spatial Position

2013 ◽  
Vol 281 ◽  
pp. 14-18 ◽  
Author(s):  
Zhen Yang ◽  
Ming Jun Wu ◽  
Fang Wang ◽  
Li Zhang ◽  
Li Na Gong
Keyword(s):  
Edge Detection ◽  
Geometric Model ◽  
Digital Camera ◽  
Calibration Method ◽  
Spatial Position ◽  
Monocular Vision ◽  
Feature Points ◽  
Intrinsic Parameter ◽  
Extrinsic Parameter ◽  
Parameter Matrix

In this paper, a method on monocular vision for spatial position is presented. The geometric model of digital camera is built and decomposed to intrinsic and extrinsic parameter matrixes under a certain assumption. Firstly, the intrinsic parameter matrix of camera is determined. Then, the extrinsic parameter matrix is solved according to the information of image. The edge detection operators are worked and in order to detect the accuracy of this method, the point of some feature points are obtained by using the principle of least squares. Compared with the conventional calibration method, this method is simple, fast and robust.

Foot Shape Reconstruction Based on a Monocular System Using Structured Light Projection

2009 ◽  
Vol 16-19 ◽  
pp. 340-346
Author(s):  
Ying Jie Ke ◽  
Li Jun Li ◽  
Kai Yong Jiang
Keyword(s):  
Rapid Prototyping ◽  
Reverse Engineering ◽  
Structured Light ◽  
Digital Camera ◽  
Shape Reconstruction ◽  
Target Object ◽  
Triangulation Method ◽  
Custom Made ◽  
Optical Triangulation ◽  
Camera Parameters

Reverse engineering has an increasing use in shoemaking process for rapid prototyping of shoe lasts. Foot shape reconstruction is one of the most important techniques in custom-made scheme. A system for reconstruction a foot shape from its 2D views using a coded structured light projection combining with the optical triangulation method is presented. A set of multiple gray coded patterns are projected to the target object through a projector and the distorted stripes patterns produced by its surface are captured by a digital camera. By adopting the optical triangulation method with the projector-camera parameters known in advance, the foot shape surface is reconstructed. The results show that the implemented system is able to reconstruct dense and precise 3D foot shapes.

A Robust Feature Points Matching Algorithm in 3D Optical Measuring System

2011 ◽  
Vol 383-390 ◽  
pp. 5193-5199 ◽  
Author(s):  
Jian Ying Yuan ◽  
Xian Yong Liu ◽  
Zhi Qiang Qiu
Keyword(s):  
3D Reconstruction ◽  
Digital Camera ◽  
Image Data ◽  
Epipolar Geometry ◽  
Bundle Adjustment ◽  
Measuring System ◽  
Feature Points ◽  
3 Dimensional ◽  
Feature Points Matching ◽  
Optical Measuring

In optical measuring system with a handheld digital camera, image points matching is very important for 3-dimensional(3D) reconstruction. The traditional matching algorithms are usually based on epipolar geometry or multi-base lines. Mistaken matching points can not be eliminated by epipolar geometry and many matching points will be lost by multi-base lines. In this paper, a robust algorithm is presented to eliminate mistaken matching feature points in the process of 3D reconstruction from multiple images. The algorithm include three steps: (1) pre-matching the feature points using constraints of epipolar geometry and image topological structure firstly; (2) eliminating the mistaken matching points by the principle of triangulation in multi-images; (3) refining camera external parameters by bundle adjustment. After the external parameters of every image refined, repeat step (1) to step (3) until all the feature points been matched. Comparative experiments with real image data have shown that mistaken matching feature points can be effectively eliminated, and nearly no matching points have been lost, which have a better performance than traditonal matching algorithms do.

Neural Network-Based Metaheuristic Parameterization with Application to the Vehicle Matching Problem in Ride-Hailing Services

2019 ◽  
Vol 2673 (10) ◽  
pp. 311-320
Author(s):  
Arslan Ali Syed ◽  
Irina Gaponova ◽  
Klaus Bogenberger
Keyword(s):  
Neural Network ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Computation Time ◽  
Problem Instance ◽  
Neighborhood Search ◽  
Matching Problem ◽  
Solution Quality ◽  
Actual Problem ◽  
Parameter Values

The majority of transportation problems include optimizing some sort of cost function. These optimization problems are often NP-hard and have an exponential increase in computation time with the increase in the model size. The problem of matching vehicles to passenger requests in ride hailing (RH) contexts typically falls into this category.Metaheuristics are often utilized for such problems with the aim of finding a global optimal solution. However, such algorithms usually include lots of parameters that need to be tuned to obtain a good performance. Typically multiple simulations are run on diverse small size problems and the parameters values that perform the best on average are chosen for subsequent larger simulations.In contrast to the above approach, we propose training a neural network to predict the parameter values that work the best for an instance of the given problem. We show that various features, based on the problem instance and shareability graph statistics, can be used to predict the solution quality of a matching problem in RH services. Consequently, the values corresponding to the best predicted solution can be selected for the actual problem. We study the effectiveness of above described approach for the static assignment of vehicles to passengers in RH services. We utilized the DriveNow data from Bavarian Motor Works (BMW) for generating passenger requests inside Munich, and for the metaheuristic, we used a large neighborhood search (LNS) algorithm combined with a shareability graph.

scholarly journals Charuco Board-Based Omnidirectional Camera Calibration Method

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 421 ◽  
Author(s):  
Gwon An ◽  
Siyeong Lee ◽  
Min-Woo Seo ◽  
Kugjin Yun ◽  
Won-Sik Cheong ◽  
...  
Keyword(s):  
Camera Calibration ◽  
Mean Absolute Error ◽  
Three Dimensional ◽  
Absolute Error ◽  
Calibration Method ◽  
Feature Points ◽  
Omnidirectional Camera ◽  
Reprojection Error ◽  
Conventional Methods ◽  
Better Than

In this paper, we propose a Charuco board-based omnidirectional camera calibration method to solve the problem of conventional methods requiring overly complicated calibration procedures. Specifically, the proposed method can easily and precisely provide two-dimensional and three-dimensional coordinates of patterned feature points by arranging the omnidirectional camera in the Charuco board-based cube structure. Then, using the coordinate information of the feature points, an intrinsic calibration of each camera constituting the omnidirectional camera can be performed by estimating the perspective projection matrix. Furthermore, without an additional calibration structure, an extrinsic calibration of each camera can be performed, even though only part of the calibration structure is included in the captured image. Compared to conventional methods, the proposed method exhibits increased reliability, because it does not require additional adjustments to the mirror angle or the positions of several pattern boards. Moreover, the proposed method calibrates independently, regardless of the number of cameras comprising the omnidirectional camera or the camera rig structure. In the experimental results, for the intrinsic parameters, the proposed method yielded an average reprojection error of 0.37 pixels, which was better than that of conventional methods. For the extrinsic parameters, the proposed method had a mean absolute error of 0.90° for rotation displacement and a mean absolute error of 1.32 mm for translation displacement.

Mobile Robot Regulation With Image Based Visual Servoing

2018 ◽  
Author(s):  
Aaron Hao Tan ◽  
Abdulrahman Al-Shanoon ◽  
Haoxiang Lang ◽  
Moustafa El-Gindy
Keyword(s):  
Visual Servoing ◽  
Target Object ◽  
Feature Points ◽  
Matlab Simulation ◽  
The Past ◽  
Vision Sensors ◽  
Servo Controller ◽  
Differential Drive Robot ◽  
Proportional Controller ◽  
Mobile Base

The development of image processing algorithms grew exponentially over the past few decades with improvements in vision sensors and computational power. In this paper, a visual servo controller is designed and developed using the image-based method for a differential drive robot. The objective is to reach a desired pose relative to a target object placed in the world frame with four feature points. A full system model that includes the mobile base and camera is presented along with the design of a proportional controller. The system is implemented in the Husky A200 Robot by Clearpath Robotics. MATLAB Simulation and experimental results are analyzed and discussed with conclusion and future works recommendation in the end.

scholarly journals Calibration Method for Monitoring Hygro-Mechanical Reactions of Pine and Oak Wood by Acoustic Emission Nondestructive Testing

Materials ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 3775
Author(s):  
Chiara Bertolin ◽  
Lavinia de Ferri ◽  
Filippo Berto
Keyword(s):  
Acoustic Emission ◽  
Brittle Fracture ◽  
Digital Camera ◽  
Calibration Method ◽  
Tensile Tests ◽  
Damage Effect ◽  
Fracture Mechanisms ◽  
Dynamic Surface ◽  
Hardening Mechanism

The main issue of wood is its sensitivity to Relative Humidity (RH) variations, affecting its dimensional stability, and thus leading to crack formations and propagations. In situ structural health monitoring campaigns imply the use of portable noninvasive techniques such as acoustic emission, used for real-time detection of energy released when cracks form and grow. This paper proposes a calibration method, i.e., acoustic emission, as an early warning tool for estimating the length of new formed cracks. The predictability of ductile and brittle fracture mechanisms based on acoustic emission features was investigated, as well as climate-induced damage effect, leading to a strain-hardening mechanism. Tensile tests were performed on specimens submitted to a 50% RH variation and coated with chemicals to limit moisture penetration through the radial surfaces. Samples were monitored for acoustic emission using a digital camera to individuate calibration curves that correlated the total emitted energy with the crack propagation, specifically during brittle fracture mechanism, since equations provide the energy to create a new surface as the crack propagates. The dynamic surface energy value was also evaluated and used to define a Locus of Equilibrium of the energy surface rate for crack initiation and arrest, as well as to experimentally demonstrate the proven fluctuation concept.

Based on the Experimental Platform of Litchi Picking Vision Calibration

2013 ◽  
Vol 462-463 ◽  
pp. 978-983
Author(s):  
Jiang Zhou Zhang ◽  
Jian Feng Zhang ◽  
Ji Zhong Deng
Keyword(s):  
Binocular Vision ◽  
Calibration Method ◽  
Feature Points ◽  
Camera Model ◽  
Reference Coordinate System ◽  
Experimental Platform ◽  
Hardware System ◽  
Mechanical Hand ◽  
Planar Pattern ◽  
Selection Of

This paper constructs the picking mechanical hand binocular vision hardware system. Using an internal and external parameters calibration method of separation. In the calibration process, with calibration planar pattern translatory manner, appropriate for extracting feature points in the calibration template, through experiment and calculation to obtain the accurate parameters of camera model; external parameters calibration is a reasonable selection of reference coordinate system, through experimental analysis to obtain the two cameras outside parameter model.

Single Beacon Indoor Localization System Based on Counter-Synchronized Compass and RSSI

2014 ◽  
Vol 627 ◽  
pp. 217-222
Author(s):  
Kok Seng Eu ◽  
Kian Meng Yap ◽  
Tiam Hee Tee
Keyword(s):  
Indoor Localization ◽  
Target Item ◽  
Optimal Solution ◽  
Research Area ◽  
Target Object ◽  
Localization Algorithm ◽  
Distance Information ◽  
Localization Method ◽  
Localization System ◽  
Lost And Found

Indoor localization system has been a popular research area in recent decades and many of them are based on multiple beacons localization method. However, there are some special applications to which the multiple beacons method is not an optimal solution due to its overdesign and cost of redundancy. Multiple beacons method uses at least three transducers and each transducer’s location must be known to find the location of a target object by using either Triangulation or Trilateration calculation. When the multiple beacons method is applied in an items lost and found system, the precise Cartesian coordinates of a target item can be found, but it is definitely overdesign and incurring redundant cost. It is due to the fact that the target item requires only two simple information i.e. Clock orientation and distance information; therefore, single beacon is enough for the task. In this paper, we propose a single beacon localization method to optimize the solution in the items lost and found system by utilizing clock orientation and estimated distance information. The proposed single beacon localization algorithm has been demonstrated and proven that it can be one of the optimal solutions for items lost and found system.

Human–robot shared control for humanoid manipulator trajectory planning

2020 ◽  
Vol 47 (3) ◽  
pp. 395-407 ◽  
Author(s):  
Yuanchao Zhu ◽  
Canjun Yang ◽  
Qianxiao Wei ◽  
Xin Wu ◽  
Wei Yang
Keyword(s):  
Control Process ◽  
Optimal Solution ◽  
Target Object ◽  
Mapping Method ◽  
Shared Control ◽  
Control Mode ◽  
Content Type ◽  
Working Space ◽  
Single Target ◽  
Human Robot Collaboration

Purpose This paper aims to propose an intuitive shared control strategy to control a humanoid manipulator that can fully combine the advantages of humans and machines to produce a stronger intelligent form. Design/methodology/approach The working space of an operator’s arm and that of a manipulator are matched, and a genetic algorithm that limits the position of the manipulator’s elbow joint is used to find the optimal solution. Then, the mapping of the operator’s action to that of manipulators is realized. The controls of the human and robot are integrated. First, the current action of the operator is input. Second, the target object is predicted according to the maximum entropy hypothesis. Third, the joint angle of the manipulator is interpolated based on time. Finally, the confidence and weight of the current moment are calculated. Findings The modified weight adjustment method is the optimal way to adjust the weight during the task. In terms of time and accuracy, the experimental results of single target obstacle avoidance grabbing and multi-target predictive grabbing show that the shared control mode can provide full play to the advantages of humans and robots to accomplish the target task faster and more accurately than the control merely by a human or robot on its own. Originality/value A flexible and highly anthropomorphic human–robot action mapping method is proposed, which provides operator decisions in the shared control process. The shared control between human and the robot is realized, and it enhances the rapidity and intelligence, paving a new way for a novel human–robot collaboration.

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