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Multi-camera vision systems: Pose es...

Chen, Chong.

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Multi-camera vision systems: Pose estimation and plenoptic imaging.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Multi-camera vision systems: Pose estimation and plenoptic imaging./
作者:	Chen, Chong.
面頁冊數:	120 p.
附註:	Source: Dissertation Abstracts International, Volume: 71-08, Section: B, page: 5010.
Contained By:	Dissertation Abstracts International71-08B.
標題:	Engineering, Electronics and Electrical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3417336
ISBN:	9781124137469

Multi-camera vision systems: Pose estimation and plenoptic imaging.
Chen, Chong.

Multi-camera vision systems: Pose estimation and plenoptic imaging. - 120 p.

Source: Dissertation Abstracts International, Volume: 71-08, Section: B, page: 5010.

Thesis (Ph.D.)--University of Illinois at Chicago, 2010.

A method is introduced to track the object's motion and estimate its pose directly from 2D image sequences. Scale-Invariant Feature Transform (SIFT) is used to extract corresponding feature points from image sequences. We demonstrate that pose estimation from the corresponding feature points can be formed as a solution to Sylvester's equation.

ISBN: 9781124137469Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Multi-camera vision systems: Pose estimation and plenoptic imaging.
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245 1 0 $a Multi-camera vision systems: Pose estimation and plenoptic imaging.
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500 $a Source: Dissertation Abstracts International, Volume: 71-08, Section: B, page: 5010.
500 $a Adviser: Dan Schonfeld.
502 $a Thesis (Ph.D.)--University of Illinois at Chicago, 2010.
520 $a A method is introduced to track the object's motion and estimate its pose directly from 2D image sequences. Scale-Invariant Feature Transform (SIFT) is used to extract corresponding feature points from image sequences. We demonstrate that pose estimation from the corresponding feature points can be formed as a solution to Sylvester's equation.
520 $a We then extend this method to estimate the object's pose from multiple cameras. We first demonstrate that centralized pose estimation from the collection of corresponding feature points in the 2D images from all cameras can be obtained as a solution to a generalized Sylvester's equation. We subsequently derive a distributed solution to pose estimation from multiple cameras and show that it is equivalent to the solution of the centralized pose estimation based on Sylvester's equation.
520 $a We also present a general framework for analyzing plenoptic sampling by investigating the spectral analysis of plenoptic imaging. The proposed framework provides a unified representation that generalizes several existing methods for plenoptic sampling, including lightfield and concentric mosaic.
590 $a School code: 0799.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Multimedia Communications. $3 1057801
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