A Flexible Pinhole Camera Model for Coherent Nonuniform Sampling

2014 ◽  
Vol 34 (4) ◽  
pp. 30-41
Author(s):  
Voicu Popescu ◽  
Bedrich Benes ◽  
Paul Rosen ◽  
Jian Cui ◽  
Lili Wang
Keyword(s):  
Nonuniform Sampling ◽  
Pinhole Camera ◽  
Camera Model

The General Pinhole Camera: Effective and Efficient Nonuniform Sampling for Visualization

2010 ◽  
Vol 16 (5) ◽  
pp. 777-790 ◽  
Author(s):  
Voicu Popescu ◽  
Paul Rosen ◽  
Laura Arns ◽  
Xavier Tricoche ◽  
Chris Wyman ◽  
...  
Keyword(s):  
Nonuniform Sampling ◽  
Pinhole Camera

Determining Intrinsic Parameters and Pose of Cameras from Single View with Variable Focal Length

2014 ◽  
Vol 635-637 ◽  
pp. 1011-1017
Author(s):  
Gui Hua Liu ◽  
Hui Min Long
Keyword(s):  
Focal Length ◽  
Pinhole Camera ◽  
Projection Matrix ◽  
Camera Model ◽  
Intrinsic Parameter ◽  
Simulation Data ◽  
Single View ◽  
Estimated Parameters ◽  
Orientation Matrix ◽  
Camera Location

This study claims an algorithm of calibration which is executed on the basis of projection matrix. This algorithm directly estimates intrinsic parameter on the basis of rotation matrix’s unitary orthogonality combined with Cholesky decomposition from the obtained projection matrix. Then, false is excluded by rotation matrix’s determinant constraints, and ultimately, camera location and orientation matrix are obtained and estimated parameters are optimized with the minimum error of reprojection residual being cost function. This algorithm is taken under a pinhole camera model and can calibrate the camera from single view with variable focal length. Both simulation data and true image experiments have proved the feasibility and robustness of this algorithm.

Camera Calibration Technique Based on HALCON Machine Vision

2013 ◽  
Vol 365-366 ◽  
pp. 666-671
Author(s):  
Xue Ping Liu ◽  
Yi Chang Chen ◽  
Zu Fu Pang
Keyword(s):  
Machine Vision ◽  
Camera Calibration ◽  
Pinhole Camera ◽  
Camera Model ◽  
Calibration Technique ◽  
Distortion Factor ◽  
Full Account ◽  
Practical Applications ◽  
Model Instance ◽  
Cross Platform

According to the perspective projection performed by a pinhole camera, taking full account of the lens radial distortion factor, the transformation between the camera coordinate has been analyzed. Combining with camera model instance of surface mount devices, the system uses Halcon machine vision software which has a powerful geometric and image computing functions to solve the camera calibration parameters and the accuracy of calibration results has been verified in practical applications. This method has advantages of computational efficiency and good value of cross-platform porting applications.

Measurement of Cam Spacing on Assembled Camshaft Based on Improved Fundamental Matrix Calibration

2013 ◽  
Vol 850-851 ◽  
pp. 241-244
Author(s):  
Guan Nan Li ◽  
Qing Chang Tan ◽  
Si Yuan Liu
Keyword(s):  
Fundamental Matrix ◽  
Ccd Camera ◽  
Calibration Method ◽  
Measurement Model ◽  
Pinhole Camera ◽  
Epipolar Line ◽  
Camera Model ◽  
Distortion Model ◽  
Imaging Model ◽  
Measurement Results

Imaging model of double CCD camera based on pinhole camera model and distortion model is introduced, and the fundamental matrix is presented. Distortion model is led into the fundamental matrix calibration. Based on the imaging model of Z. Zhangs calibration method, fundamental matrix is carried out. Pixel coordinate for calibration is modified by cameras interior parameters and distortion coefficients. Base on the imaging model of double CCD camera, measurement model for cam spacing is established. Cam spacing is measured by the feature of cam edge. In experiments, accurate pixel coordinates of model plane were used in calibration. The distance between a point and its corresponding epipolar line was estimated as the error. The measurement results show that the accuracy of proposed method satisfied the monitoring requirements of the axial positioning error of the cam piece.

Pinhole Camera Model

2014 ◽  
pp. 610-613 ◽  
Author(s):  
Peter Sturm
Keyword(s):  
Pinhole Camera ◽  
Camera Model

scholarly journals Conception of a C-Arm Parametrization Device Evaluated by an Inverse Registration Approach: An application for 2D/3D Registration in Minimally Invasive Surgery

2021 ◽  
Vol 7 (1) ◽  
pp. 26-29
Author(s):  
Julio C. Alvarez-Gomez ◽  
Hubert Roth ◽  
Jürgen Wahrburg
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Invasive Surgery ◽  
Average Distance ◽  
Pinhole Camera ◽  
Testing Device ◽  
3D Registration ◽  
Camera Model ◽  
X Ray ◽  
Intrinsic And Extrinsic Parameters

Abstract Camera resectioning is the process of finding the intrinsic and extrinsic parameters of the pinhole camera model. A mobile X-ray device (C-arm) can be represented with the pinhole camera model. The C-arm parameters can be determined with a parametrization device and the direct linear transformation (DLT) algorithm. We present the conception process of a parametrization device and further optimizations of the DLT algorithm. The evaluation of the parametrization quality is carried out with an inverse registration approach on a testing device. The seven landmarks in the testing device are compared on an X-ray image and a digitally reconstructed radiograph (DRR). The average distance of the corresponding landmarks between imaging modalities is 2.5 pixels. This deviation indicates an adequate design of the parametrization device for a 2D/3D registration in minimally invasive surgery.

scholarly journals On the Position Determination of Docking Station for AUVs Using Optical Sensor and Neural Network

2020 ◽  
Vol 10 (1) ◽  
pp. 15-24
Author(s):  
Thieu Quang Minh Nhat ◽  
Hyeung-Sik Choi ◽  
Mai The Vu ◽  
Joono Sur ◽  
Jin-Il Kang ◽  
...  
Keyword(s):  
Neural Network ◽  
Light Source ◽  
Optical Sensor ◽  
Unmanned Vehicles ◽  
Pinhole Camera ◽  
Camera Model ◽  
Camera System ◽  
System A ◽  
Better Than

Detecting the relative position of the docking station is a very important issue for the homing of AUVs (Autonomous Unmanned Vehicles). To detect the position of the light source, a pinhole camera model structure was proposed like the camera model. However, due to the sensor resolution and the distortion errors of the pinhole camera system, the application of the camera of docking the under turbid sea environments is almost impossible. In this paper, a new method detecting the position of the docking station using a light source is presented. Also, a newly developed optical sensor which makes it much easier to sense the light source than the camera system for homing of the AUV under the water is performed. In addition, to improve the system, a neural network (NN) algorithm constructing a model relating the light inputs and optical sensor which are developed in this study is proposed. To evaluate the performance of the NN algorithm, the experiments were performed in the air beforehand. The result shows that the NN algorithm with AUV docking system using the NN model is better than the pinhole camera model.

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