Review of constraints on vision-based gesture recognition for human–computer interaction

dc.contributor.authorChakraborty, Biplab Ketan
dc.contributor.authorSarma, Debajit
dc.contributor.authorBhuyan, M. K.
dc.contributor.authorMacDorman, Karl F.
dc.contributor.departmentHuman-Centered Computing, School of Informatics and Computingen_US
dc.date.accessioned2018-11-20T18:58:26Z
dc.date.available2018-11-20T18:58:26Z
dc.date.issued2018-01
dc.description.abstractThe ability of computers to recognise hand gestures visually is essential for progress in human-computer interaction. Gesture recognition has applications ranging from sign language to medical assistance to virtual reality. However, gesture recognition is extremely challenging not only because of its diverse contexts, multiple interpretations, and spatio-temporal variations but also because of the complex non-rigid properties of the hand. This study surveys major constraints on vision-based gesture recognition occurring in detection and pre-processing, representation and feature extraction, and recognition. Current challenges are explored in detail.en_US
dc.eprint.versionAuthor's manuscripten_US
dc.identifier.citationChakraborty, B. K., Sarma, D., Bhuyan, M. K., & MacDorman, K. F. (2018). Review of constraints on vision-based gesture recognition for human–computer interaction. IET Computer Vision, 12(1), 3–15. https://doi.org/10.1049/iet-cvi.2017.0052en_US
dc.identifier.urihttps://hdl.handle.net/1805/17801
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.isversionof10.1049/iet-cvi.2017.0052en_US
dc.relation.journalIET Computer Visionen_US
dc.rightsPublisher Policyen_US
dc.sourceAuthoren_US
dc.subjectfeature extractionen_US
dc.subjectgesture recognitionen_US
dc.subjectman-machine systemsen_US
dc.titleReview of constraints on vision-based gesture recognition for human–computer interactionen_US
dc.typeArticleen_US
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