RETRACTED: Machine learning based sign language recognition: a review and its research frontier (Retracted Article)

被引:34
|
作者
Elakkiya, R. [1 ]
机构
[1] SASTRA Deemed Be Univ, Ctr Informat Super Highway CISH, Sch Comp, Thanjavur 613401, India
关键词
Sign language recognition; Subunit framework; Feature extraction; Movement epenthesis; Machine learning; HIDDEN MARKOV-MODELS; FACIAL EXPRESSION RECOGNITION; 3D HAND POSE; GESTURE RECOGNITION; REAL-TIME; COMPUTER-VISION; FEATURE-EXTRACTION; WAVELET TRANSFORM; NEURAL-NETWORKS; BASIC UNITS;
D O I
10.1007/s12652-020-02396-y
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the recent past, research in the field of automatic sign language recognition using machine learning methods have demonstrated remarkable success and made momentous progression. This research article investigates the impact of machine learning in the state of the art literature on sign language recognition and classification. It highlights the issues faced by the present recognition system for which the research frontier on sign language recognition intends the solutions. In this article, around 240 different approaches have been compared that explore sign language recognition for recognizing multilingual signs. The research done by various authors is also studied, and some of the important research articles are also discussed in this article. Based on the inferences from these approaches, this article discussed how machine learning methods could benefit the field of automatic sign language recognition and the potential gaps that machine learning approaches need to address for the real-time sign language recognition.
引用
收藏
页码:7205 / 7224
页数:20
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