• pravin m
• robin r
• naveen kumar s
• tharun bhaskar
• jenifershylaja

To distinguish between various hand gestures and classify them effectively in order to comprehend both static and dynamic hand movements utilized in communication. Initially, gesture recognition equipment such as accelerometers, Sensor devices, hand movement sensors, and connected electrodes are used to record both static and dynamic hand movements. Hand gesture detection technologies including surface electromyogram, latent regression forest, dynamic temporal warping framework, multivariate fuzzy decision tree, hidden Markov models (HMM), and support vector machine are used to process these motions. Gesture capture systems that have the right lighting conditions are able to record hand movements done with both single and two hands. These recorded motions are examined for occlusions and finger-to-finger contacts in order to determine which gesture is correct, categorize it, and disregard sporadic movements.

Human-computer interaction, Hand gestures, Gesture recognition system, Static and dynamic hand gesture.

"hand gesture recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.i127-i131, June-2024, Available :http://www.jetir.org/papers/JETIR2406814.pdf

"hand gesture recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. ppi127-i131, June-2024, Available at : http://www.jetir.org/papers/JETIR2406814.pdf