Challenges and opportunities in finger spelling recognition in air

Gedam, Shruti; Shrawankar, Urmila

doi:10.1109/icimia.2017.7975543

Cited by 4 publications

(1 citation statement)

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“…The final method allows you to write numerous letters consecutively one on top of the other inside the same hypothetical box. We look at this paper's singular writing style [71]. To suggest a some new technique for air-writing recognition that solves these problems and uses a webcam or a normal laptop camera as the VHS input.…”

Section: Fig 1 Flow Chart Of Proposed Airwriting Systemmentioning

confidence: 99%

A Survey on Air Writing Character Recognition and Translation

R S,

C K,

V P

et al. 2023

IJEAST

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Computer systems are increasingly using airwriting recognition since it can be done quickly and intelligently. The term "air-writing acknowledgment apparatus" refers to the use of a stylus to draw an articulated character or expression in free space. This study presents a simple yet effective convolutional neural network-based air-writing recognition method (CNN). It is suggested to use a plausible algorithm tracking hands to reward air-writing circles captured through a web camera. This study provides a straightforward but efficient method for recognizing air-writing that uses deep convolutional neural networks (CNNs). With the aid of hand motions, users can write characters in the air that are subsequently translated into written text using an air writing character recognition and translation technology. Convolutional neural networks (CNN), which are trained to recognise and decipher human hand gestures, power this technology. The device uses a camera to record the hand movements and then runs the data through CNN to identify the characters being typed. The identified characters are then converted into text that may be presented on a screen using text-to-speech technology.

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Section: Fig 1 Flow Chart Of Proposed Airwriting Systemmentioning

confidence: 99%