Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/25749

TitleA comparison of machine learning algorithms applied to hand gesture recognition
Author(s)Trigueiros, Paulo
Ribeiro, António Fernando
Reis, L. P.
KeywordsMachine vision
Image processing
Machine learning
Hand gesture recognition
Issue date2012
PublisherAssociação Ibérica de Sistemas e Tecnologias de Informação (AISTI)
JournalIberian Conference on Information Systems and Technologies, CISTI
Abstract(s)Hand gesture recognition for human computer interaction is an area of active research in computer vision and machine learning. The primary goal of gesture recognition research is to create a system, which can identify specific human gestures and use them to convey information or for device control. This paper presents a comparative study of four classification algorithms for static hand gesture classification using two different hand features data sets. The approach used consists in identifying hand pixels in each frame, extract features and use those features to recognize a specific hand pose. The results obtained proved that the ANN had a very good performance and that the feature selection and data preparation is an important phase in the all process, when using lowresolution images like the ones obtained with the camera in the current work.
TypeConference paper
URIhttp://hdl.handle.net/1822/25749
ISBN9789899624771
ISSN2166-0727
Peer-Reviewedyes
AccessOpen access
Appears in Collections:DEI - Artigos em atas de congressos internacionais

Files in This Item:
File Description SizeFormat 
CI35.pdfDocumento principal2,14 MBAdobe PDFView/Open

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID