A Survey on Hand Gesture Recognition Using Machine Learning and Infrared Information

• Published in: Applied Technologies pp. 297 - 311
• Main Authors: Nogales, Rubén, Benalcázar, Marco E.
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing
• Series: Communications in Computer and Information Science
• Subjects: Hand gesture recognition; Infrared information; Machine learning; Survey; Systematic literature review
• ISBN: 9783030425197; 3030425193
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-030-42520-3_24

The research consists in the hand gestures are movements that convey information and thus complement oral communication or by themselves constitute a form of communication between people. The function of a hand gesture recognition system is to identify the type of movement, from a given set of movements, and the instant when that movement is performed. Gesture recognition systems have multiple applications including sign language translation, bionics, human-machine interaction, gamming, and virtual reality. For this reason, hand gesture recognition is a problem where many researchers have focused their attention too. In this context, in this paper, we present a systematic literature review for hand gesture recognition using ma-chine learning and infrared information. This work has been made because there is no work in the scientific literature that reviews gesture recognition systems based on machine learning and infrared information. In this work, we answer the research question: what is the architecture of the proposed models for hand gesture recognition based on machine learning and infrared information? For answering this research question, we used Kitchenham methodology. Finally, in this work, we also present trends and gaps with respect to the problem analyzed.