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The development of computer vision technology in recent days, enhanced the human-computer interface (HCI) systems in a broad spectrum. The recent developments of human computer interfacing such as Augmented reality applications, gesture-based control devices, robotic assistants, patient health care monitoring systems considers human body pose estimation as important process involved in it. The growth of neural computing and artificial intelligence (AI) models plays an optimum role in development of HCI and pose estimation. The presented study considers various existing challenges in body language recognition systems and its role in communication quality enhancement. The comprehensive study considers existing state of art approaches and its drawbacks, challenges, technology, tool in terms of achieving better accuracy and formulated a robust human pose estimation model using machine learning technology. The suggested architecture and solutions derived from the proposed method are well explored in the article.
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Maharasi et al. (2024) studied this question.
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