Competitive neural networks applied to face localization
Cuevas, Erik V ;  Zaldivar, Daniel ;  Rojas, Raúl ;  Universität <Berlin, Freie Universität> / Fachbereich Mathematik und Informatik

Main titleCompetitive neural networks applied to face localization
AuthorCuevas, Erik V
AuthorZaldivar, Daniel
AuthorRojas, Raúl
InstitutionUniversität <Berlin, Freie Universität> / Fachbereich Mathematik und Informatik
No. of Pages11 S.
Series Freie Universität Berlin, Fachbereich Mathematik und Informatik : Ser. B, Informatik ; [20]03,13
Classification (DDC)004 Data processing and Computer science
AbstractColor-segmentation is very sensitive to changes in the intensity of light. Many
algorithms do not tolerate variations in color hue which correspond, in fact, to the
same object. Learning Vector Quantization (LVQ) networks learn to recognize groups
of similar input vectors in such a way that neurons physically near to each other in
the neuron layer respond to similar input vectors. Learning is supervised, the inputs
vectors into target classes are chosen by the user. In this work a new algorithm based on
LVQ is presented. It involves neural networks that operate directly on the image pixels
with a decision function. This algorithm has been applied to spotting and tracking
human faces, and shows more robustness than other algorithms for the same task.
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FU DepartmentDepartment of Mathematics and Computer Science
Other affiliation(s)Institut für Informatik
Year of publication2003
Type of documentWorking paper
Terms of use/Rights Nutzungsbedingungen
Created at2009-05-13 : 09:03:35
Last changed2015-03-03 : 01:39:51
Static URLhttp://edocs.fu-berlin.de/docs/receive/FUDOCS_document_000000001917