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Australian Sign Language Recognition Using Moment Invariants

机译：使用矩不变量的澳大利亚手语识别

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Human Computer Interaction is geared towards seamless human machine integration without the need for LCDs, Keyboards or Gloves. Systems have already been developed to react to limited hand gestures especially in gaming and in consumer electronics control. Yet, it is a monumental task in bridging the well-developed sign languages in different parts of the world with a machine to interpret the meaning. One reason is the sheer extent of the vocabulary used in sign language and the sequence of gestures needed to communicate different words and phrases. Auslan the Australian Sign Language is comprised of numbers, finger spelling for words used in common practice and a medical dictionary. There are 7415 words listed in Auslan website. This research article tries to implement recognition of numerals using a computer using the static hand gesture recognition system developed for consumer electronics control at the University of Wollongong in Australia. The experimental results indicate that the numbers, zero to nine can be accurately recognized with occasional errors in few gestures. The system can be further enhanced to include larger numerals using a dynamic gesture recognition system.
机译：人机交互旨在实现无缝的人机集成，而无需LCD，键盘或手套。已经开发了对有限手势做出反应的系统，尤其是在游戏和消费电子控制中。然而，这是一项具有里程碑意义的任务，那就是用一台机器来解释世界上各个地方的发达手语。原因之一是手语所用词汇的绝对范围以及传达不同单词和短语所需的手势顺序。澳大利亚手语Auslan由数字，常用惯例中的单词的手指拼写和医学词典组成。 Auslan网站上列出了7415个单词。这篇研究文章试图使用计算机来实现数字识别，该计算机使用的是澳大利亚卧龙岗大学为消费电子控制开发的静态手势识别系统。实验结果表明，零到九个数字可以准确识别，很少出现手势错误。使用动态手势识别系统，可以进一步增强该系统以包括更大的数字。

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