Abstract
Gesture recognition is critical in human-computer communication. As observed, a plethora of current technological developments are in the works, including biometric authentication, which we see all the time in our smartphones. Hand gesture focus, a frequent human-computer interface in which we manage our devices by presenting our hands in front of a webcam, can benefit people of different backgrounds. Some of the efforts in human-computer interface include voice assistance and virtual mouse implementation with voice commands, fingertip recognition and hand motion tracking based on an image in a live video. Human Computer Interaction (HCI), particularly vision-based gesture and object recognition, is becoming increasingly important. Hence, we focused to design and develop a system for monitoring fingers using extreme learning-based hand gesture recognition techniques. Extreme learning helps in quickly interpreting the hand gestures with improved accuracy which would be a highly useful in the domains like healthcare, financial transactions and global business
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