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Fusion of RGB and thermal data for i...

Mississippi State University.

Fusion of RGB and thermal data for improved scene understanding.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Fusion of RGB and thermal data for improved scene understanding./
作者:	Smith, Ryan E.
面頁冊數:	1 online resource (69 pages)
附註:	Source: Masters Abstracts International, Volume: 56-04.
標題:	Electrical engineering. -
電子資源:	click for full text (PQDT)
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. - 1 online resource (69 pages)

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

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

Includes bibliographical references

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.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369706215Subjects--Topical Terms:

596380
Electrical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Fusion of RGB and thermal data for improved scene understanding.
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100 1 $a Smith, Ryan E. $3 1148510
245 1 0 $a Fusion of RGB and thermal data for improved scene understanding.
264 0 $c 2017
300 $a 1 online resource (69 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
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.
504 $a Includes bibliographical references
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.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Electrical engineering. $3 596380
655 7 $a Electronic books. $2 local $3 554714
690 $a 0544
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Mississippi State University. $b Electrical and Computer Engineering. $3 1148511
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10267781 $z click for full text (PQDT)

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