Hands free : a wearable in-air gesture recognition system

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2016

Author dc:creator

• Chang, Matthew (Matthew J.)

Advisor dc:contributor.advisor

• Chris Schmandt.

• Electrical Engineering and Computer Science.

Statement 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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/112819

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/112819