Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/39057

TitleGeneric system for human-computer gesture interaction
Author(s)Trigueiros, Paulo
Ribeiro, António Fernando
Reis, L. P.
KeywordsHuman-computer interaction
Gesture interfaces
Generic systems
Computer vision
Machine learning
Issue dateMay-2014
PublisherIEEE
Abstract(s)Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.
TypeConference paper
URIhttp://hdl.handle.net/1822/39057
DOI10.1109/ICARSC.2014.6849782
Publisher versionhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6849782
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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