scholarly journals Multi-camera System Calibration with Built-in Relative Orientation Constraints (Part 2) Automation, Implementation, and Experimental Results

2014 ◽  
Vol 32 (3) ◽  
pp. 205-216 ◽  
Author(s):  
Zahra Lari ◽  
Ayman Habib ◽  
Mehdi Mazaheri ◽  
Kaleel Al-Durgham
Keyword(s):  
Relative Orientation ◽  
Experimental Results ◽  
Camera System ◽  
System Calibration

scholarly journals Calibration of multi-camera photogrammetric systems

2014 ◽  
Vol XL-1 ◽  
pp. 101-108 ◽  
Author(s):  
I. Detchev ◽  
M. Mazaheri ◽  
S. Rondeel ◽  
A. Habib
Keyword(s):  
Stability Analysis ◽  
Low Cost ◽  
A Priori ◽  
Relative Orientation ◽  
System Stability ◽  
Specific System ◽  
Camera System ◽  
System Calibration ◽  
System Stability Analysis ◽  
Orientation Parameters

Due to the low-cost and off-the-shelf availability of consumer grade cameras, multi-camera photogrammetric systems have become a popular means for 3D reconstruction. These systems can be used in a variety of applications such as infrastructure monitoring, cultural heritage documentation, biomedicine, mobile mapping, as-built architectural surveys, etc. In order to ensure that the required precision is met, a system calibration must be performed prior to the data collection campaign. This system calibration should be performed as efficiently as possible, because it may need to be completed many times. Multi-camera system calibration involves the estimation of the interior orientation parameters of each involved camera and the estimation of the relative orientation parameters among the cameras. This paper first reviews a method for multi-camera system calibration with built-in relative orientation constraints. A system stability analysis algorithm is then presented which can be used to assess different system calibration outcomes. The paper explores the required calibration configuration for a specific system in two situations: major calibration (when both the interior orientation parameters and relative orientation parameters are estimated), and minor calibration (when the interior orientation parameters are known a-priori and only the relative orientation parameters are estimated). In both situations, system calibration results are compared using the system stability analysis methodology.

Visual Feedback for Nonholonomic Mobile Robots

2010 ◽  
pp. 152-181 ◽  
Author(s):  
Andrea Usai ◽  
Paolo Di Giamberardino
Keyword(s):  
Mobile Robots ◽  
State Estimation ◽  
Visual Feedback ◽  
Fundamental Matrix ◽  
Experimental Results ◽  
System State ◽  
Head Pose ◽  
Nonholonomic Mobile Robots ◽  
Camera System ◽  
Observer Accuracy

In this chapter, we describe a homography approach to vision based feedback for nonholonomic mobile robots control. Differently than other approaches based on homography or fundamental matrix, our method has been developed to be robust to reference features loss, during the robot movement. This allows us to implement an arbitrary control law without the need of a teach-by-showing stage. In the chapter, the use of a stereo camera system to improve the observer accuracy and to perform an auto-calibration of the stereo-head pose is investigated. Experimental results are provided to show the performances of the proposed system state estimation, using an eye-in-hand mobile robotic platform.

Rapid and non-invasive surface crack detection for pressed-panel products based on online image processing

2019 ◽  
Vol 18 (5-6) ◽  
pp. 1928-1942 ◽  
Author(s):  
Hwee Kwon Jung ◽  
Gyuhae Park
Keyword(s):  
Image Processing ◽  
Manufacturing Process ◽  
Crack Detection ◽  
Experimental Results ◽  
Inspection System ◽  
Camera System ◽  
Non Invasive ◽  
Panel Products ◽  
Traditional Approaches ◽  
Detection And Localization

Crack detection during the manufacturing process of pressed-panel products is an important aspect of quality management. Traditional approaches for crack detection of those products are subjective and expensive because they are usually performed by experienced human inspectors. Therefore, the development and implementation of an automated and accurate inspection system is required for the manufacturing process. In this article, a crack detection technique based on image processing is proposed that utilizes the images of panel products captured by a regular camera system. First, the binary panel object image is extracted from various backgrounds after considering the color factor. Edge lines are then generated from a binary image using a percolation process. Finally, crack detection and localization is performed with a unique edge-line evaluation. In order to demonstrate the capability of the proposed technique, lab-scale experiments were carried out with a thin aluminum plate. In addition, a test was performed with the panel images acquired at an actual press line. Experimental results show that the proposed technique could effectively detect panel cracks at an improved rate and speed. The experimental results also demonstrate that the proposed technique could be an extension of structural health monitoring frameworks into a new manufacturing application.

scholarly journals 3D visual perception for self-driving cars using a multi-camera system: Calibration, mapping, localization, and obstacle detection

2017 ◽  
Vol 68 ◽  
pp. 14-27 ◽  
Author(s):  
Christian Häne ◽  
Lionel Heng ◽  
Gim Hee Lee ◽  
Friedrich Fraundorfer ◽  
Paul Furgale ◽  
...  
Keyword(s):  
Visual Perception ◽  
Obstacle Detection ◽  
Camera System ◽  
System Calibration ◽  
Self Driving Cars

Single Camera Stereo with Planar Mirrors

2013 ◽  
Vol 684 ◽  
pp. 447-450
Author(s):  
Yu Yan ◽  
Bing Wei He
Keyword(s):  
Gaussian Noise ◽  
Symmetry Plane ◽  
Relative Orientation ◽  
Experimental Results ◽  
Single Camera ◽  
Stereo Images ◽  
Matlab Toolbox ◽  
The Real ◽  
Planar Mirrors ◽  
New System

This paper presents a new system for rapidly acquiring stereo images using a single camera and a pair of planar mirrors (catadioptric stereo). Firstly, the camera used to capture images is calibrated with matlab toolbox. Secondly, the position and pose of the planar mirrors relative to the fixed, calibrated camera is estimated, and this procedure is accomplished by calculating the symmetry plane of the real and reflected image corners of a chessboard. Thirdly, the relative orientation of two reflected virtual cameras is obtained. Finally, Gaussian noise is added to the image corners of the chessboard to verify the performance of the established stereo system. Experimental results show the effectiveness and robustness of our system.

scholarly journals CALIBRATION STUDY OF A TRIMBLE ACx4 SYSTEM FOR DIRECT GEOREFERENCING MAPPING APPLICATIONS

2018 ◽  
Vol IV-1 ◽  
pp. 45-52
Author(s):  
L. E. Filho ◽  
E. A. Mitishita
Keyword(s):  
Large Scale ◽  
Calibration Method ◽  
Relative Orientation ◽  
Aerial Images ◽  
Synthetic Image ◽  
Integrated Sensor ◽  
Full Field ◽  
System Calibration ◽  
Simultaneous Acquisition ◽  
Sensor Orientation

<p><strong>Abstract.</strong> The Trimble Aerial Camera x4 (i.e., TACx4) is a photogrammetric multi-head system manufactured by Trimble Inc.&amp;copy; in 2010. It has four cameras mounted together in the main structure allowing the simultaneous acquisition to generate a single synthetic image with much larger ground coverage. In addition, the cameras are also integrated with a GNSS/INS to perform “Direct” or “Integrated” Sensor Orientation. The main condition to obtain photogrammetric mapping products with high accuracy using a direct sensor orientation procedure is to execute a step known as “geometric system calibration”. In general, the photogrammetric multi-head system manufacturers perform this step using laboratory methods to obtain the parameters of cameras interior and relative orientation. Accurate mounting parameters (lever arms and “boresight misalignments”) are fundamental requirements to generate the synthetic image when georeferencing of images is applied. This paper shows a “full field” calibration method to perform the geometric system calibration of the TACx4 system and its evaluation for direct sensor orientation mapping applications. The developed method involves two steps using only aerial images: (1) estimation of the cameras interior and relative orientation parameters to generate the synthetic image and (2) estimation of the synthetic image interior orientation and the mounting parameters between the synthetic image and GNSS/INS reference systems using two different methods. The obtained results in the conventional photogrammetric project show that the proposed method allows performing the geometric system calibration of the TACx4 system achieving around 50<span class="thinspace"></span>cm (5 pixels) in horizontal and vertical accuracies. The obtained results can be used for large-scale mapping requirements using direct sensor orientation according to Brazilian accuracy standards.</p>

Sign in / Sign up

Export Citation Format

Share Document