Face recognition by multi-frame fusion of rotating heads in videos

Canavan, Shaun

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dc.contributor.author	Canavan, Shaun
dc.contributor.other	Youngstown State University. Department of Computer Science and Information Systems. OCLC No.: 250739850
dc.date.accessioned	2021-10-15T15:53:49Z
dc.date.available	2021-10-15T15:53:49Z
dc.date.issued	2008
dc.identifier.other	B20314942
dc.identifier.other	250739850
dc.identifier.uri	https://jupiter.ysu.edu:443/record=b2031494
dc.identifier.uri	http://hdl.handle.net/1989/16636
dc.description	vii, 20 leaves : ill. ; 29 cm. Thesis (M.S.)--Youngstown State University, 2008. Includes bibliographical references (leaves 17-19).	en_US
dc.description.abstract	This paper presents a face recognition study that implicitly utilizes the 3D information in 2D video sequences through a multi-sample fusion process. The approach is based on the hypothesis that continuous and coherent intensity variations in video frames caused by a rotating head can provide information similar to that of explicit face models or shapes from range images. The multi-frame fusion was performed on both the image and score levels. Both types of fusion showed large improvements in the recognition rates. The image level fusion showed improvements from 91%, using one frame, to 100%, using 7 frames, under regular lighting. An improvement from 63%, using one frame, to 85%, using 7 frames, was noticed under strong shadow. The score level fusion of two frames also showed an improvement in the recognition rate.	en_US
dc.description.sponsorship	Youngstown State University. Department of Computer Science and Information Systems.	en_US
dc.language.iso	en_US	en_US
dc.relation.ispartofseries	Master's Theses;no. 0983
dc.subject	Human face recognition (Computer science)	en_US
dc.subject	Biometric identification.	en_US
dc.title	Face recognition by multi-frame fusion of rotating heads in videos	en_US
dc.type	Thesis	en_US

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