This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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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
The ability to identify unoccupied resources in the radio spectrum is a key capability for opportunistic users in a cognitive radio environment. This paper draws upon and extends geometrically based ideas in statistical signal processing to develop estimators for the rank and the occupied subspace in a multi-user environment from

The ability to identify unoccupied resources in the radio spectrum is a key capability for opportunistic users in a cognitive radio environment. This paper draws upon and extends geometrically based ideas in statistical signal processing to develop estimators for the rank and the occupied subspace in a multi-user environment from multiple temporal samples of the signal received at a single antenna. These estimators enable identification of resources, such as the orthogonal complement of the occupied subspace, that may be exploitable by an opportunistic user. This concept is supported by simulations showing the estimation of the number of users in a simple CDMA system using a maximum a posteriori (MAP) estimate for the rank. It was found that with suitable parameters, such as high SNR, sufficient number of time epochs and codes of appropriate length, the number of users could be correctly estimated using the MAP estimator even when the noise variance is unknown. Additionally, the process of identifying the maximum likelihood estimate of the orthogonal projector onto the unoccupied subspace is discussed.
ContributorsBeaudet, Kaitlyn (Author) / Cochran, Douglas (Thesis advisor) / Turaga, Pavan (Committee member) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Created2014