Sign language recognition using micro-Doppler and explainable deep learning

McCleary, James and Parra García, Laura and Ilioudis, Christos and Clemente, Carmine; (2021) Sign language recognition using micro-Doppler and explainable deep learning. In: 2021 IEEE Radar Conference (RadarConf21). IEEE Radar Conference . IEEE, USA. ISBN 9781728176093 (https://doi.org/10.1109/RadarConf2147009.2021.9455...)

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Abstract

In this paper, Sign Language Recognition and classification of the micro-Doppler signatures of different British Sign Language (BSL) gestures is studied. A database of four different BSL hand gesture motions is presented in the form of micro-Doppler signals, recorded with a continuous waveform radar. For detecting the presence of the micro-Doppler signatures, joint time-frequency is applied by calculating their spectrograms. Each individual gesture is expected to contain unique spectral characteristics that are exploited in order to classify the gestures. A deep learning approach with transfer learning is studied and discussed for carrying out the classification task. Following this, a novel explainable AI algorithm is implemented to give the user visual feedback, in the form of colour highlights, for the most relevant features used to classify each signal.

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