Camera Self-Calibration with Planar Pattern Using Genetic Algorithm

2011 ◽  
Vol 130-134 ◽  
pp. 1833-1838 ◽  
Author(s):  
Chun Hao Kao ◽  
Rong Ching Lo
Keyword(s):  
Genetic Algorithm ◽  
Fitness Function ◽  
Optimization Methods ◽  
Calibration Method ◽  
Natural Scenes ◽  
Self Calibration ◽  
Specific Object ◽  
Calibration Pattern ◽  
Conventional Optimization ◽  
Optimum Solution

In the paper, a stereo camera self-calibration method with Genetic Algorithm (GA) applied to the navigation of autonomous land vehicle (ALV) in a natural environment is proposed. The proposed method does not require specific object as a calibration pattern, e.g. checkerboard; conversely, it exploits common feature, for example: planes among natural scenes. In the evaluating process of GA, the coplanar condition of 3D points is employed as a fitness function to inspect the camera parameters. In addition, real valued GA is used because it does not only decrease the complexity of encoding and decoding process, but also increase the precision of solution. Comparing to conventional optimization methods, the camera self-calibration method based on GA can avoid being trapped in local minimum and does not need initial value or gradient information. Several experiments of the camera calibration with the stereo vision show that the proposed method can find approximate optimum solution.

An Automatic Self-Calibration Approach for Wide Baseline Stereo Cameras Using Sea Surface Images

2015 ◽  
Vol 03 (04) ◽  
pp. 277-290 ◽  
Author(s):  
Han Wang ◽  
Wei Mou ◽  
Xiaozheng Mou ◽  
Shenghai Yuan ◽  
Soner Ulun ◽  
...  
Keyword(s):  
Feature Detection ◽  
Depth Estimation ◽  
Calibration Method ◽  
Sea Surface ◽  
Distant Object ◽  
Self Calibration ◽  
Calibration Pattern ◽  
Left And Right ◽  
Calibration Approach ◽  
Surface Images

Stereo rig with wide baseline is necessary when accurate depth estimation for distant object is desired. However, in order to make calibration pattern to be viewed from both left and right cameras, the wider the baseline the bigger the calibration pattern is required. In contrast to the traditional stereo calibration method using calibration pattern, we propose a self-calibration approach that can estimate cameras' rotation matrices for stereo rig with wide baseline (3 m). Given images taken from left and right cameras, the relative roll and pitch angles between two cameras are recovered by aligning sea horizon in left and right images. The pitch angle is estimated by making the projections of one point at infinite distance appear at the same location in both images. A photometric minimization is applied to refine the rotation parameters. Compared with conventional checkerboard-based calibration techniques which require extra equipments or personnel, our approach only needs a pair of sea images. Moreover, unlike most self-calibration approaches, feature detection and matching are not required which makes it possible to apply our approach on featureless images. As a result, it is flexible and easy to implement our approach on sea surface images. Real world experiments demonstrate the feasibility of our approach.

scholarly journals Genetic Algorithm Application in Optimization of Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Ali Norouzi ◽  
A. Halim Zaim
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Fitness Function ◽  
Optimization Methods ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Final Formula ◽  
Nonlinear Optimization Methods

There are several applications known for wireless sensor networks (WSN), and such variety demands improvement of the currently available protocols and the specific parameters. Some notable parameters are lifetime of network and energy consumption for routing which play key role in every application. Genetic algorithm is one of the nonlinear optimization methods and relatively better option thanks to its efficiency for large scale applications and that the final formula can be modified by operators. The present survey tries to exert a comprehensive improvement in all operational stages of a WSN including node placement, network coverage, clustering, and data aggregation and achieve an ideal set of parameters of routing and application based WSN. Using genetic algorithm and based on the results of simulations in NS, a specific fitness function was achieved, optimized, and customized for all the operational stages of WSNs.

scholarly journals Online IMU Self-Calibration for Visual-Inertial Systems

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1624 ◽  
Author(s):  
Yao Xiao ◽  
Xiaogang Ruan ◽  
Jie Chai ◽  
Xiaoping Zhang ◽  
Xiaoqing Zhu
Keyword(s):  
Inertial Sensor ◽  
Low Cost ◽  
Optimization Methods ◽  
Calibration Method ◽  
Measurement Unit ◽  
Intrinsic Parameters ◽  
Self Calibration ◽  
Calibration Problem ◽  
System States ◽  
Inertial Systems

Low-cost microelectro mechanical systems (MEMS)-based inertial measurement unit (IMU) measurements are usually affected by inaccurate scale factors, axis misalignments, and g-sensitivity errors. These errors may significantly influence the performance of visual-inertial methods. In this paper, we propose an online IMU self-calibration method for visual-inertial systems equipped with a low-cost inertial sensor. The goal of our method is to concurrently perform 3D pose estimation and online IMU calibration based on optimization methods in unknown environments without any external equipment. To achieve this goal, we firstly develop a novel preintegration method that can handle the IMU intrinsic parameters error propagation. Then, we frame IMU calibration problem into general factors so that we can easily integrate the factors into the current graph-based visual-inertial frameworks and jointly optimize the IMU intrinsic parameters as well as the system states in a big bundle. We evaluate the proposed method with a publicly available dataset. Experimental results verify that the proposed approach is able to accurately calibrate all the considered parameters in real time, leading to significant improvement of estimation precision of visual-inertial system (VINS) compared with the estimation results with offline precalibrated IMU measurements.

scholarly journals Research on Multistage Rotor Assembly Optimization Methods for Aeroengine Based on the Genetic Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yue Chen ◽  
Jiwen Cui ◽  
Xun Sun ◽  
Shihai Cui
Keyword(s):  
Genetic Algorithm ◽  
Fitness Function ◽  
Spatial Location ◽  
Optimization Methods ◽  
Optimization Method ◽  
Propagation Model ◽  
Optimization Strategy ◽  
Assembly Method ◽  
Alignment Process ◽  
Rotor Assembly

The coaxiality and unbalance are the two important indexes to evaluate the assembly quality of an aeroengine. It often needs to be tested and disassembled repeatedly to meet the double-objective requirements at the same time. Therefore, an intelligent assembly method is urgently needed to directly predict the optimal assembly orientations of the rotors at each stage to meet the double-objective requirements simultaneously. In this study, an assembly optimization method for the multistage rotor of an aeroengine is proposed based on the genetic algorithm. Firstly, a spatial location propagation model is developed to accurately predict the spatial position of each rotor after assembly. The alignment process of the assembly screw holes of the adjacent rotors is considered for the first time. Secondly, a new assembly optimization strategy is proposed to select different assembly data for the specific values of the coaxiality and unbalance, respectively. Finally, a double-objective fitness function is constructed based on the coaxiality and unbalance. The simulation and experimental results show that the assembly optimization method proposed in this study can be utilized to achieve synchronous optimization of the coaxiality and unbalance of an aeroengine during preassembly.

A self-calibration method for rotary tables’ five degrees-of-freedom error motions

Measurement ◽  
2021 ◽  
Vol 174 ◽  
pp. 109067
Author(s):  
Zhi-Feng Lou ◽  
Li Liu ◽  
Ji-Yun Zhang ◽  
Kuang-chao Fan ◽  
Xiao-Dong Wang
Keyword(s):  
Degrees Of Freedom ◽  
Calibration Method ◽  
Self Calibration
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