In past years, there were a lot of researches made in order to provide more accurate andcomfortable interaction between human and machine. Developing a system which recognizeshuman gestures, is an important study to improve interaction between human and machine.Sign language is a way of communication for hearing-impaired people which enables them tocommunicate among themselves and with other people around them. Sign language consists ofhand gestures and facial expressions. During the past 20 years, researches were made tofacilitate communication of hearing-impaired people with others.Sign language recognition systems are designed in various countries. This paper presents a signlanguage recognition system, which uses Kinect camera to obtain skeletal model. Our aim wasto recognize expressions, which are used widely in Turkish Sign Language (TSL). For thatpurpose we have selected 15 words/expressions randomly (repeated 4 times each by 3 differentsigners) which belong to Turkish Sign Language. We have used 180 records in total. Videos arerecorded using Microsoft Kinect Camera and Nui Capture. Joint angles and joint positions havebeen used as features of gesture and achieved close to 100% recognition rates.
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