Applying teeline shorthand using leap motion controller
dc.contributor.author | Zang, Weikai | |
dc.date.accessioned | 2018-03-21T14:11:30Z | |
dc.date.available | 2018-03-21T14:11:30Z | |
dc.date.issued | 2017-02-08 | |
dc.description.abstract | A hand gesture recognition program was developed to recognize users’ Teeline shorthand gestures as English letters, words and sentences using Leap Motion Controller. The program is intended to provide a novel way for the users to interact with electronics by waving gestures in the air to input texts instead of using keyboards. In the recognition mode, the dynamic time warping algorithm is used to compare the similarities between different templates and gesture inputs and summarize the recognition results; in the edit process, users are able to build their own gestures to customize the commands. A series of experiment results show that the program can achieve a considerable recognition accuracy, and it has consistent performance in face of different user groups. | en_CA |
dc.description.degree | Master of Science (MSc) in Computational Sciences | en_CA |
dc.identifier.uri | https://laurentian.scholaris.ca/handle/10219/2961 | |
dc.language.iso | en | en_CA |
dc.publisher.grantor | Laurentian University of Sudbury | en_CA |
dc.subject | Human-computer interaction | en_CA |
dc.subject | teeline shorthand | en_CA |
dc.subject | leap motion controller | en_CA |
dc.subject | dynamic time warping | en_CA |
dc.subject | hand gesture recognition | en_CA |
dc.title | Applying teeline shorthand using leap motion controller | en_CA |
dc.type | Thesis | en_CA |
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