Real-Time Alphabet Hand Gesture Detection System

Nowadays, gesture identification is a dare to feature effluence and pattern recognizance, in which a movement is classified. The response of a gesture recognition system might help address difficulties in domains including medical, robotics, sign language, human-computer interfaces, virtual reality, augmented reality, and security. This paper provides a thorough literature review of hand gesture detection based on infrared data and machine learning techniques in this context. This is an expanded version of the work presented at the 2019 ICSE conference. The Kitchen ham technique was used to create this systematic literature review. This comprehensive literature review identifies the architectures of the models, the methodologies utilized in each module, and the kind of learning employed (supervised, unsupervised, etc.).