Finger placement correction for static gesture recognition in American Sign Language

WCU Author/Contributor (non-WCU co-authors, if there are any, appear on document)
Veronica Yenquenida Flamenco Cordova (Creator)
Institution
Western Carolina University (WCU )
Web Site: http://library.wcu.edu/
Advisor
Robert Adams

Abstract: Within the past few years, research involving gesture recognition has flourished and has led to new and improved programs assisting people who communicate with sign language [1–8]. Although numerous approaches have been developed for recognizing gestures [5, 6, 9], very little attention has been focused on American Sign Language (ASL) training for correcting the placement of individual fingers. Although, it is easy to mimic gestures, it is difficult to know whether or not you are signing them correctly. This is important in that most gestures, if made slightly incorrect, convey a completely different word, letter, or meaning [10]. This research involved developing a computer program to assist in teaching the correct placement of the fingers when performing ASL. Considering sign language has a wide range of gestures, the focus of the study is on static gestures which include a few letters of the alphabet. In order for the program to recognize finger placement, the user must wear colored latex over the fingertips. Then by using image processing techniques along with different algorithms, ASL hand gestures made by the user will be compared to standard images in a database. The program will provide feedback concerning how close the user is to the reference gesture as well as specific instructions concerning how to correct the gesture. This is the first step in developing a training/teaching program to help teach sign language accurately and precisely without the need of face-to-face instruction. Future studies could lead to more accurate training techniques for a wider range of ASL gestures.

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Additional Information

Publication
Thesis
Language: English
Date: 2014
Subjects
American Sign Language -- Study and teaching -- Computer programs
American Sign Language -- Study and teaching -- Technological innovations
American Sign Language -- Computer-assisted instruction