Abstract
One of the most commonly studied subjects in today’s world is air writing or gesture recognition in the air. Gesture recognition in the air requires the detection of the alphabet or number that is being written and correctly predicted. In this paper, if a person makes a specific gesture with a finger, the gesture is recognized, and all gestures correspond to a certain alphabet that triggers certain actions in the surrounding area, such as turning on the appliances. Here, we have built a cheap and powerful motion capture device at home to execute a desired operation with the flick of our finger. Using a standard night vision camera (a modified Raspberry Pi camera), Raspberry Pi, CNN, OpenCV computer vision library and machine learning, we have achieved a device that recognizes characters in a three-dimensional space with six degrees of freedom. The proposed system achieves 94.77% accuracy in the recognition rate when tested with English alphabets and numbers.
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Ghosh, S., Mitra, A. (2022). Air Writing-Based Automated Room. In: Kolhe, M.L., Jaju, S.B., Diagavane, P.M. (eds) Smart Technologies for Energy, Environment and Sustainable Development, Vol 1. Springer Proceedings in Energy. Springer, Singapore. https://doi.org/10.1007/978-981-16-6875-3_53
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DOI: https://doi.org/10.1007/978-981-16-6875-3_53
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