Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Last Update2002: administrator
Metadata Last Update2020: administrator
Citation KeyFerisCesa:2000:TrFaFe
TitleTracking facial features using Gabor wavelet networks
Access Date2021, Jan. 25
Number of Files1
Size641 KiB
Context area
Author1 Feris, Rogério S.
2 Cesar Junior, Roberto M.
EditorCarvalho, Paulo Cezar Pinto
Walter, Marcelo
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 13 (SIBGRAPI)
Conference LocationGramado, RS, Brazil
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
OrganizationSBC - Brazilian Computer Society
History2008-07-17 14:10:49 :: administrator -> banon ::
2008-08-26 15:23:00 :: banon -> administrator ::
2009-08-13 20:36:50 :: administrator -> banon ::
2010-08-28 20:00:08 :: banon -> administrator ::
2020-02-19 02:58:51 :: administrator -> :: 2000
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Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
Keywordsoptical tracking, video sequences, Gabor wavelet networks, automatic facial feature tracking, discrete face template, linear combination, continuous 2D odd-Gabor wavelet functions, 2D parameters, image information, homogeneous illumination changes, affine deformations, face image, tracking approach, face geometry, facial feature deformations, eye blinking, smiling, computational resources, real time processing.
AbstractThe work presents a method for automatic facial feature tracking in video sequences. In this method, a discrete face template is represented as a linear combination of continuous 2D odd-Gabor wavelet functions. The weights and 2D parameters (position, scale and orientation) of each wavelet are determined optimally so that the maximum amount of image information is preserved for a given number of wavelets. We have used this representation to achieve effective facial feature tracking that is robust to homogeneous illumination changes and affine deformations of the face image. Moreover, the tracking approach considers the overall geometry of the face, being robust to facial feature deformations such as eye blinking and smiling. The number of wavelets in the representation may be chosen with respect to the available computational resources, even allowing real time processing.
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NotesThe conference was held in Gramado, RS, Brazil, from October 17 to 20.
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