Sign Language Recognition with the Kinect Sensor Based on Conditional Random Fields

Sensors

关键词: sign language recognition;    conditional random field;    BoostMap embedding;   

DOI  :  10.3390/s150100135

来源: mdpi

【 摘 要 】

Sign language is a visual language used by deaf people. One difficulty of sign language recognition is that sign instances of vary in both motion and shape in three-dimensional (3D) space. In this research, we use 3D depth information from hand motions, generated from Microsoft's Kinect sensor and apply a hierarchical conditional random field (CRF) that recognizes hand signs from the hand motions. The proposed method uses a hierarchical CRF to detect candidate segments of signs using hand motions, and then a BoostMap embedding method to verify the hand shapes of the segmented signs. Experiments demonstrated that the proposed method could recognize signs from signed sentence data at a rate of 90.4%.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.