| dc.contributor.advisor | Chris Schmandt. | en_US |
| dc.contributor.author | Chang, Matthew (Matthew J.) | en_US |
| dc.contributor.other | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. | en_US |
| dc.date.accessioned | 2017-12-20T17:23:58Z | |
| dc.date.available | 2017-12-20T17:23:58Z | |
| dc.date.copyright | 2016 | en_US |
| dc.date.issued | 2016 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1721.1/112819 | |
| dc.description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016. | en_US |
| dc.description | This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. | en_US |
| dc.description | Cataloged from student-submitted PDF version of thesis. | en_US |
| dc.description | Includes bibliographical references (pages 38-39). | en_US |
| dc.description.abstract | In this thesis I present my work in developing a wearable gesture interface for mobile devices with limited sensing capabilites. The proposed method utilizes a novel form of color invariant processing to augment traditional convolutional neural networks for gesture recognition. This techniques allows the system to perform color invariant recognition avoiding traditional issues with hand segmentation. Using this method several demo applications were prototyped on a mobile phone platform to test its real-time efficacy. Through a preliminary user study we confirmed that this method allows static gesture recognition in a wide variety of mobile scenarios. | en_US |
| dc.description.statementofresponsibility | by Matthew Chang. | en_US |
| dc.format.extent | 41 pages | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Massachusetts Institute of Technology | en_US |
| dc.rights | MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. | en_US |
| dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
| dc.subject | Electrical Engineering and Computer Science. | en_US |
| dc.title | Hands free : a wearable in-air gesture recognition system | en_US |
| dc.title.alternative | Wearable in-air gesture recognition system | en_US |
| dc.type | Thesis | en_US |
| dc.description.degree | M. Eng. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
| dc.identifier.oclc | 1014181181 | en_US |
