Computer Science ›› 2019, Vol. 46 ›› Issue (11A): 299-302.

• Pattern Recognition & Image Processing • Previous Articles     Next Articles

Continuous Sign Language Sentence Recognition Based on Double Transfer Probability of Key Actions

LI Chen1, HUANG Yuan-yuan1, HU Zuo-jin2   

  1. (College of Computer Science and Technology,Nanjing University of Aeronautics & Astronautics,Nanjing 210016,China)1;
    (College of Math and Information Science,Nanjing Normal University of Special Education,Nanjing 210038,China)2
  • Online:2019-11-10 Published:2019-11-20

Abstract: At present,the most difficult problem in continuous sign language recognition is how to split out the words effectively.In this paper,key actions were regarded as the basic units of sign language and an algorithm based on double transfer probability of key actions was proposed.After acquiring the sequence of basic units from continuous sign language,the boundaries of words can be effectively found by judging the intra-word and inter-word transfer relations of all adjacent basic units.Then the sequence of basic units are segmented by these boundaries and the candidate words of each group of basic units can be identified.Finally,according to the transfer probabilities between candidate words of different groups,the probability of corresponding synthetic sentence is calculated and then the final recognition result is output by the principle of maximum probability.The algorithm is easy to implement and has high execution efficiency.It can be applied to non-specific population through experimental verification.

Key words: Sign language sentence, Key actions, Transfer probability

CLC Number: 

  • TP391.41
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