Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Anderson, Derek T.
Committee Member
Bethel, Cindy L.
Committee Member
Archibald, Christopher.
Committee Member
Ball, John E.
Date of Degree
5-6-2017
Document Type
Graduate Thesis - Open Access
Major
Electrical and Computer Engineering
Degree Name
Master of Science (M.S.)
College
James Worth Bagley College of Engineering
Department
Department of Electrical and Computer Engineering
Abstract
Thermal cameras are used in numerous computer vision applications, such as human detection and scene understanding. However, the cost of high quality and high resolution thermal sensors is often a limiting factor. Conversely, high resolution visual spectrum cameras are readily available and generally inexpensive. Herein, we explore the creation of higher quality upsampled thermal imagery using a high resolution visual spectrum camera and Markov random fields theory. This paper also presents a discussion of the tradeoffs from this approach and the effects of upsampling, both from quantitative and qualitative perspectives. Our results demonstrate the successful application of this approach for human detection and the accurate propagation of thermal measurements within images for more general tasks like scene understanding. A tradeoff analysis of the costs related to performance as the resolution of the thermal camera decreases are also provided.
URI
https://hdl.handle.net/11668/16610
Recommended Citation
Smith, Ryan Elliott, "Fusion of RGB and Thermal Data for Improved Scene Understanding" (2017). Theses and Dissertations. 2364.
https://scholarsjunction.msstate.edu/td/2364