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Evaluation of video based pedestrian...

ProQuest Information and Learning Co.

Evaluation of video based pedestrian and vehicle detection algorithms.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Evaluation of video based pedestrian and vehicle detection algorithms./
作者:	Bandarupalli, Varun.
面頁冊數:	1 online resource (93 pages)
附註:	Source: Masters Abstracts International, Volume: 49-04, page: 2610.
Contained By:	Masters Abstracts International49-04.
標題:	Electrical engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9781124460604

Evaluation of video based pedestrian and vehicle detection algorithms.
Bandarupalli, Varun.

Evaluation of video based pedestrian and vehicle detection algorithms. - 1 online resource (93 pages)

Source: Masters Abstracts International, Volume: 49-04, page: 2610.

Thesis (M.S.E.E.)--University of Nevada, Las Vegas, 2010.

Includes bibliographical references

Video based detection systems rely on the ability to detect moving objects in video streams. Video based detection systems have applications in many fields like, intelligent transportation, automated surveillance etc. There are many approaches adopted for video based detection. Evaluation and selecting a suitable approach for pedestrian and vehicle detection is a challenging task. While evaluating the object detection algorithms, many factors should be considered in order to cope with unconstrained environments, non stationary background, different object motion patterns and the variation in types of object being detected.

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

Mode of access: World Wide Web

ISBN: 9781124460604Subjects--Topical Terms:

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

554714
Electronic books.

Evaluation of video based pedestrian and vehicle detection algorithms.
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100 1 $a Bandarupalli, Varun. $3 1189486
245 1 0 $a Evaluation of video based pedestrian and vehicle detection algorithms.
264 0 $c 2010
300 $a 1 online resource (93 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: 49-04, page: 2610.
500 $a Adviser: Venkatesan Muthukumar.
502 $a Thesis (M.S.E.E.)--University of Nevada, Las Vegas, 2010.
504 $a Includes bibliographical references
520 $a Video based detection systems rely on the ability to detect moving objects in video streams. Video based detection systems have applications in many fields like, intelligent transportation, automated surveillance etc. There are many approaches adopted for video based detection. Evaluation and selecting a suitable approach for pedestrian and vehicle detection is a challenging task. While evaluating the object detection algorithms, many factors should be considered in order to cope with unconstrained environments, non stationary background, different object motion patterns and the variation in types of object being detected.
520 $a In this thesis, we implement and evaluate different video based detection algorithms used for pedestrian and vehicle detection. Video based pedestrian and vehicle detection involves object detection through background foreground segmentation and object tracking. For background foreground segmentation, frame differencing, background averaging, mixture of Gaussians and codebook methods were implemented. For object tracking, Mean-Shift tracking and Lucas Kanade optical flow tracking algorithms were implemented.
520 $a The performance of each of these algorithms is evaluated by a comparative study; based on their performance such as ability to get good detection and tracking, CodeBook algorithm is selected as a candidate algorithm for background foreground segmentation and Mean-Shift tracking is used to track the detected objects for pedestrian and vehicle detection.
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 University of Nevada, Las Vegas. $b Electrical Engineering. $3 1189487
773 0 $t Masters Abstracts International $g 49-04.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1488671 $z click for full text (PQDT)

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