Matching Items (3)
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Description
Fisheye cameras are special cameras that have a much larger field of view compared to

conventional cameras. The large field of view comes at a price of non-linear distortions

introduced near the boundaries of the images captured by such cameras. Despite this

drawback, they are being used increasingly in many applications of computer

Fisheye cameras are special cameras that have a much larger field of view compared to

conventional cameras. The large field of view comes at a price of non-linear distortions

introduced near the boundaries of the images captured by such cameras. Despite this

drawback, they are being used increasingly in many applications of computer vision,

robotics, reconnaissance, astrophotography, surveillance and automotive applications.

The images captured from such cameras can be corrected for their distortion if the

cameras are calibrated and the distortion function is determined. Calibration also allows

fisheye cameras to be used in tasks involving metric scene measurement, metric

scene reconstruction and other simultaneous localization and mapping (SLAM) algorithms.

This thesis presents a calibration toolbox (FisheyeCDC Toolbox) that implements a collection of some of the most widely used techniques for calibration of fisheye cameras under one package. This enables an inexperienced user to calibrate his/her own camera without the need for a theoretical understanding about computer vision and camera calibration. This thesis also explores some of the applications of calibration such as distortion correction and 3D reconstruction.
ContributorsKashyap Takmul Purushothama Raju, Vinay (Author) / Karam, Lina (Thesis advisor) / Turaga, Pavan (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Camera calibration has applications in the fields of robotic motion, geographic mapping, semiconductor defect characterization, and many more. This thesis considers camera calibration for the purpose of high accuracy three-dimensional reconstruction when characterizing ball grid arrays within the semiconductor industry. Bouguet's calibration method is used following a set of criteria

Camera calibration has applications in the fields of robotic motion, geographic mapping, semiconductor defect characterization, and many more. This thesis considers camera calibration for the purpose of high accuracy three-dimensional reconstruction when characterizing ball grid arrays within the semiconductor industry. Bouguet's calibration method is used following a set of criteria with the purpose of studying the method's performance according to newly proposed standards. The performance of the camera calibration method is currently measured using standards such as pixel error and computational time. This thesis proposes the use of standard deviation of the intrinsic parameter estimation within a Monte Carlo simulation as a new standard of performance measure. It specifically shows that the standard deviation decreases based on the increased number of images input into the calibration routine. It is also shown that the default thresholds of the non-linear maximum likelihood estimation problem of the calibration method require change in order to improve computational time performance; however, the accuracy lost is negligable even for high accuracy requirements such as ball grid array characterization.
ContributorsStenger, Nickolas Arthur (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Kovvali, Narayan (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Arizona State University (Publisher)
Created2012
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Description
There is a growing interest for improved high-accuracy camera calibration methods due to the increasing demand for 3D visual media in commercial markets. Camera calibration is used widely in the fields of computer vision, robotics and 3D reconstruction. Camera calibration is the first step for extracting 3D data from a

There is a growing interest for improved high-accuracy camera calibration methods due to the increasing demand for 3D visual media in commercial markets. Camera calibration is used widely in the fields of computer vision, robotics and 3D reconstruction. Camera calibration is the first step for extracting 3D data from a 2D image. It plays a crucial role in computer vision and 3D reconstruction due to the fact that the accuracy of the reconstruction and 3D coordinate determination relies on the accuracy of the camera calibration to a great extent. This thesis presents a novel camera calibration method using a circular calibration pattern. The disadvantages and issues with existing state-of-the-art methods are discussed and are overcome in this work. The implemented system consists of techniques of local adaptive segmentation, ellipse fitting, projection and optimization. Simulation results are presented to illustrate the performance of the proposed scheme. These results show that the proposed method reduces the error as compared to the state-of-the-art for high-resolution images, and that the proposed scheme is more robust to blur in the imaged calibration pattern.
ContributorsPrakash, Charan Dudda (Author) / Karam, Lina J (Thesis advisor) / Frakes, David (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2012