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Individual 3D Face Modeling and Reco...

Nguyen, Hoang Thanh.

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Individual 3D Face Modeling and Recognition in a Video Network.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Individual 3D Face Modeling and Recognition in a Video Network./
作者:	Nguyen, Hoang Thanh.
面頁冊數:	130 p.
附註:	Source: Dissertation Abstracts International, Volume: 74-03(E), Section: B.
Contained By:	Dissertation Abstracts International74-03B(E).
標題:	Engineering, Computer. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3543829
ISBN:	9781267729927

Individual 3D Face Modeling and Recognition in a Video Network.
Nguyen, Hoang Thanh.

Individual 3D Face Modeling and Recognition in a Video Network. - 130 p.

Source: Dissertation Abstracts International, Volume: 74-03(E), Section: B.

Thesis (Ph.D.)--University of California, Riverside, 2012.

Given an uncalibrated network of video cameras, we are tasked with the problem of building a 3D model of every person's face as they move within the network. The process of doing so requires overcoming many challenges including person detection, tracking, cross-camera correspondence (how to determine if a person in one camera is the same person in another), and the final 3D model reconstruction from multiple views in real-time or at near real-time speeds (efficient modeling and data fusion from multiple hardware sources). Towards this goal, a wireless camera network was designed and built from the ground up, a new tracking algorithm and a cross-camera human signature method was developed, and face modeling using multiple cameras in a real-world setting was performed.

ISBN: 9781267729927Subjects--Topical Terms:

1669061
Engineering, Computer.

Individual 3D Face Modeling and Recognition in a Video Network.
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520 $a Given an uncalibrated network of video cameras, we are tasked with the problem of building a 3D model of every person's face as they move within the network. The process of doing so requires overcoming many challenges including person detection, tracking, cross-camera correspondence (how to determine if a person in one camera is the same person in another), and the final 3D model reconstruction from multiple views in real-time or at near real-time speeds (efficient modeling and data fusion from multiple hardware sources). Towards this goal, a wireless camera network was designed and built from the ground up, a new tracking algorithm and a cross-camera human signature method was developed, and face modeling using multiple cameras in a real-world setting was performed.
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