Towards a low-cost air-written character recognition system
Designing an embedded machine learning system to recognise the first 10 letters of the Latin alphabet
P.J. Pronk (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Q. Wang – Mentor (TU Delft - EEMS - General)
M. Yang – Coach (TU Delft - Embedded Systems)
R. Zhu – Coach (TU Delft - Embedded Systems)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
This study introduces a novel system that leverages three photodiodes and ambient light to identify air-written characters on a resource-constrained device. Through experimentation, suitable methods of data preprocessing, machine learning and model compression were selected to recognize the first 10 characters of the Latin alphabet. The final system was able to recognize these characters with a between-participant accuracy of 50.80% and a within-participant accuracy of 67.82%.