HAND GESTURE RECOGNITION USING MACHINE LEARNING ALGORITHMS
Abstract
Communication between people is an integral part of life. In the process of communication, people convey their emotions, thoughts, desires to each other. People with disabilities, such as deaf and dumb people, experience various difficulties in the process of communication [1]. Today, 5% of the world's people (more than 430 million), and in Kazakhstan more than 18 thousand people suffer from deafness. By 2050, this it is assumed will reach 700 million people around the world. Deaf or mute people use hand gestures to communicate with others, to express themselves correctly. People who speak a natural language do not always understand their actions. To understand this, we need sign language interpreters. Their number is very small, and most of them work in large cities or regional centers. The solution to these problems can be found by human computer interaction. Today, a lot of research is being carried out in this direction. To solve this problem, a lot of research is currently underway. But the program that provides the perfect two-way translation has not yet been created. Especially for people who speak in Kazakh language. In this paper will be considered classical algorithms for gesture recognition.
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