Research on Continuous Sign Language Sentence Recognition Algorithm Based on Weighted Key-Frame
Xin-Xin Xu*, Yuan-Yuan Huang*, and Zuo-Jin Hu**,
*Institute of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics
29 General Avenue, Jiangning District, Nanjing, China
**School of Mathematics and Information Science, Nanjing Normal University of Special Education
No.1 Shennong Road, Qixia District, Nanjing, China
At present, most of the dynamic sign language recognition is only for sign language words, the continuous sign language sentence recognition research and the corresponding results are less, because the segmentation of such sentence is very difficult. In this paper, a sign language sentence recognition algorithm is proposed based on weighted key-frames. Key-frames can be regarded as the basic unit of sign word, therefore, according to key frames we can get related vocabularies, and thus we can further organize these vocabularies into meaningful sentences. Such work can avoid the hard point of dividing sign language sentence directly. With the help of Kinect, i.e. motion-control device, a kind of self-adaptive algorithm of key-frame extraction based on the trajectory of sign language is brought out in the paper. After that, the key-frame is given weight according to its semantic contribution. Finally, the recognition algorithm is designed based on these weighted key-frames and thus get the continuous sign language sentence. Experiments show that the algorithm designed in this paper can realize real-time recognition of continuous sign language sentences.
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