Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/18419
DC Field | Value | |
---|---|---|
dc.title | Gesture recognition using windowed dynamic time warping | |
dc.contributor.author | HO CHUN JIAN | |
dc.date.accessioned | 2010-10-31T18:00:46Z | |
dc.date.available | 2010-10-31T18:00:46Z | |
dc.date.issued | 2010-01-21 | |
dc.identifier.citation | HO CHUN JIAN (2010-01-21). Gesture recognition using windowed dynamic time warping. ScholarBank@NUS Repository. | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/18419 | |
dc.description.abstract | In today?s world, computers and machines are ever more pervasive in our environment. Human beings are using an increasing number of electronic devices in everyday work and life. Human-Computer Interaction (HCI) has also become an important science, as there is a need to improve efficiency and effectiveness of communication of meaning between humans and machines. In particular, we are no longer restricted to using only keyboards and mice as input devices, but every part of our body, with the introduction of human body area sensor networks. The decreasing size of inertial sensors such as accelerometers, gyroscopes have enabled smaller and portable sensors to be worn on the body for motion capture. In this way, captured data is also different from the type of information given by visual-based motion capture systems. In this project, we endeavour to perform gesture recognition on quaternions, a rotational representation, instead of the usual X, Y, and Z axis information obtained from motion capture. Due to the variable lengths of gestures, dynamic time warping is performed on the gestures for recognition purposes. This technique is able to map time sequences of different lengths to each other for comparison purposes. As this is a very time-consuming algorithm, we introduce a new method known as ? Windowed Dynamic Time Warping, which exponentially increases the speed of recognition processing, along with a reduced training set, while having a comparable accuracy of recognition | |
dc.language.iso | en | |
dc.subject | Gesture Recognition, Dynamic Time Warping | |
dc.type | Thesis | |
dc.contributor.department | ELECTRICAL & COMPUTER ENGINEERING | |
dc.contributor.supervisor | WONG WAI CHOONG, LAWRENCE | |
dc.description.degree | Master's | |
dc.description.degreeconferred | MASTER OF ENGINEERING | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Master's Theses (Open) |
Show simple item record
Files in This Item:
File | Description | Size | Format | Access Settings | Version | |
---|---|---|---|---|---|---|
HoCJ.pdf | 4.33 MB | Adobe PDF | OPEN | None | View/Download |
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.