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Fusion of RGB and thermal data for i...

Smith, Ryan E.

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Fusion of RGB and thermal data for improved scene understanding.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fusion of RGB and thermal data for improved scene understanding./
Author:	Smith, Ryan E.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
Description:	69 p.
Notes:	Source: Masters Abstracts International, Volume: 56-04.
Contained By:	Masters Abstracts International56-04(E).
Subject:	Electrical engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10267781
ISBN:	9781369706215

Fusion of RGB and thermal data for improved scene understanding.
Smith, Ryan E.

Fusion of RGB and thermal data for improved scene understanding. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 69 p.

Source: Masters Abstracts International, Volume: 56-04.

Thesis (M.Eng.)--Mississippi State University, 2017.

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.

ISBN: 9781369706215Subjects--Topical Terms:

649834
Electrical engineering.

Fusion of RGB and thermal data for improved scene understanding.
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100 1 $a Smith, Ryan E. $3 3318671
245 1 0 $a Fusion of RGB and thermal data for improved scene understanding.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 69 p.
500 $a Source: Masters Abstracts International, Volume: 56-04.
500 $a Advisers: Derek T. Anderson; Cindy L. Bethel.
502 $a Thesis (M.Eng.)--Mississippi State University, 2017.
520 $a 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.
590 $a School code: 0132.
650 4 $a Electrical engineering. $3 649834
690 $a 0544
710 2 $a Mississippi State University. $b Electrical and Computer Engineering. $3 1044030
773 0 $t Masters Abstracts International $g 56-04(E).
790 $a 0132
791 $a M.Eng.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10267781