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Hand Gesture Recognition System Using Machine Learning

  • Milind Udbhav,
  • Robin Kumar Attri,
  • Prateek Garg,
  • Meenu Vijarania,
  • Swati Gupta,
  • Akshat Aggarwal

摘要

As technology is evolving and changing day by day many possibilities have become possible such as the development of smart and natural interface interactive systems between the user and computer using hand gestures. Robots are trying these techniques to mimic humans and amaze everyone with the new technological advancement and innovations helping to make communication with smart machines easier. Also, the technology has the capabilities to be used in the medical industry for the distribution of hospital resources and help to reduce dependency on translators. Using such technology is also promoting the things which were considered impossible can be achieved now with the help of integration with AR/XR platforms and more futuristic technologies for better results. Gesture recognition is playing a major role in making life easier and smart for making our day-to-day tasks with the integration with IoT devices and cloud-based systems. The hand gesture recognition system is an example of a gesture recognition system that could help speech-impaired people to reduce their dependability on a translator for communicating their ideology. With the help of a hand recognition system, non-verbal communication can be easily achieved with the control of computers. With the help of technology interacting with humans becomes very easy and convenient. Further, the technology can be extended when combined with augmented reality, cloud computing, and IoT for more practicality and real-life implementation. With the help of AI and machine learning previous records can be maintained and further improved for increasing the overall experience of the user. The main objective of the system will give the system ability to perform different functions of computer and mouse cursor functions like drag and drop and webcam functionalities with the help of virtual mouse system functionality. Techniques like image recognition of deep learning are used for performing real-time tracking. The existing system cannot just limit to its industry and company usage but doesn’t fulfill real-life functionalities, our proposed system aim is to help real-life users in the medical industry and from the prevention of car accidents to object tracing and saving many lives the use of technology of gesture system many lives can be improved and saved and given new hope of living.