Research Trends in Hand Gesture Recognition Techniques
M S Srividya1, Anala M R2

1PM S Srividya, Department of Computer Science and Engineering, R. V. College of Engineering, Bengaluru, India.
2Dr. Anala M R, Department of Computer Science and Engineering, R. V. College of Engineering, Bengaluru, India.
Manuscript received on February 02, 2020. | Revised Manuscript received on February 10, 2020. | Manuscript published on March 30, 2020. | PP: 1059-1064 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7519038620/2020©BEIESP | DOI: 10.35940/ijrte.F7519.038620

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Abstract: Over years’ key board and mouse are among the most effective input devices to the computers. Not much improvement has happened for other modes of inputs like voice and gestures. These kinds of inputs explore the limitations caused by the key board and mouse, which needs actual physical contact. With gestures and voice the physical proximity can be little relaxed and can be used by specially-abled people. Exploring effective Human Computer Interactions (HCI) has always been of great interest for development of new techniques and methods. Gestures are considered as more easy, natural, and intuitive method for communicating with systems. Hand recognition and analysis forms the core of these systems. This paper provides comparative study on state of art technologies that work in this area. The different representation, detection and recognition techniques are discussed. The strength and challenges of different techniques are highlighted. The main aim of this research is to summarize the research progress done till date with different technologies for gesture recognition algorithms, identify areas which need further research.
Keywords: Hidden Markov Model, Neural Networks, Probabilistic Models.
Scope of the Article: Routing, Switching and Addressing Techniques.