Spelling It Out: Real–Time ASL Fingerspelling Recognition
Pugeault, N and Bowden, R (2011) Spelling It Out: Real–Time ASL Fingerspelling Recognition In: ICCV 2011: 1st IEEE Workshop on Consumer Depth Cameras for Computer Vision, 2011-11-06 - 2011-11-13, Barcelona, Spain.
Available under License : See the attached licence file.
This article presents an interactive hand shape recognition user interface for American Sign Language (ASL) finger-spelling. The system makes use of a Microsoft Kinect device to collect appearance and depth images, and of the OpenNI+NITE framework for hand detection and tracking. Hand-shapes corresponding to letters of the alphabet are characterized using appearance and depth images and classified using random forests. We compare classification using appearance and depth images, and show a combination of both lead to best results, and validate on a dataset of four different users. This hand shape detection works in real-time and is integrated in an interactive user interface allowing the signer to select between ambiguous detections and integrated with an English dictionary for efficient writing.
|Item Type:||Conference or Workshop Item (Conference Paper)|
|Divisions :||Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing|
|Identification Number :||https://doi.org/10.1109/ICCVW.2011.6130290|
|Additional Information :||Copyright 2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Depositing User :||Symplectic Elements|
|Date Deposited :||22 May 2012 08:22|
|Last Modified :||09 Jun 2014 13:36|
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