A hand gesture recognition technique for human-computer interaction
buir.contributor.author | Güdükbay, Uğur | |
dc.citation.epage | 104 | en_US |
dc.citation.spage | 97 | en_US |
dc.citation.volumeNumber | 28 | en_US |
dc.contributor.author | Kılıboz, N. Ç. | en_US |
dc.contributor.author | Güdükbay, Uğur | en_US |
dc.date.accessioned | 2016-02-08T10:25:08Z | |
dc.date.available | 2016-02-08T10:25:08Z | |
dc.date.issued | 2015 | en_US |
dc.department | Department of Computer Engineering | en_US |
dc.description.abstract | We propose an approach to recognize trajectory-based dynamic hand gestures in real time for human-computer interaction (HCI). We also introduce a fast learning mechanism that does not require extensive training data to teach gestures to the system. We use a six-degrees-of-freedom position tracker to collect trajectory data and represent gestures as an ordered sequence of directional movements in 2D. In the learning phase, sample gesture data is filtered and processed to create gesture recognizers, which are basically finite-state machine sequence recognizers. We achieve online gesture recognition by these recognizers without needing to specify gesture start and end positions. The results of the conducted user study show that the proposed method is very promising in terms of gesture detection and recognition performance (73% accuracy) in a stream of motion. Additionally, the assessment of the user attitude survey denotes that the gestural interface is very useful and satisfactory. One of the novel parts of the proposed approach is that it gives users the freedom to create gesture commands according to their preferences for selected tasks. Thus, the presented gesture recognition approach makes the HCI process more intuitive and user specific. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T10:25:08Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2015 | en |
dc.identifier.doi | 10.1016/j.jvcir.2015.01.015 | en_US |
dc.identifier.issn | 1047-3203 | |
dc.identifier.uri | http://hdl.handle.net/11693/24170 | |
dc.language.iso | English | en_US |
dc.publisher | Academic Press | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1016/j.jvcir.2015.01.015 | en_US |
dc.source.title | Journal of Visual Communication and Image Representation | en_US |
dc.subject | Adaptive gestures | en_US |
dc.subject | Dynamic gesture recognition | en_US |
dc.subject | Finite state machine-based recognition | en_US |
dc.subject | Hand trajectory recognition | en_US |
dc.subject | Human-computer interaction | en_US |
dc.subject | Degrees of freedom (mechanics) | en_US |
dc.subject | Logic circuits | en_US |
dc.subject | Signal encoding | en_US |
dc.subject | Trajectories | en_US |
dc.subject | Adaptive gestures | en_US |
dc.subject | Gestural interfaces | en_US |
dc.subject | Gesture-based interaction | en_US |
dc.subject | Hand gesture | en_US |
dc.subject | Intuitive interfaces | en_US |
dc.subject | Gesture recognition | en_US |
dc.title | A hand gesture recognition technique for human-computer interaction | en_US |
dc.type | Article | en_US |
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