Using CNN and Tensorflow to recognise ‘Signal for Help’ Hand Gestures

Abstract

Domestic violence is a prevalent crime in our society, more so with the introduction of COVID19 restrictions. For the victim, it can be a traumatic experience, so much as to not report the crime. Consequently, the ‘Signal for Help’ hand gestures were recently introduced as a discrete method to enable the victim to confidently express their need for help. This research investigates the classification of these hand gestures using a deep learning approach, which has not previously been implemented in this context. A deep learning approach is chosen due to the favourable results obtained in different contexts on hand gesture classification. Due to the unavailability of a dataset containing images of these hand gestures, a ‘Signal for Help’ dataset containing 112 images is generated as part of this study. These images are pre-processed to be of size 50x50 dimensions. Furthermore, a synthetic version of this dataset is also generated from the pre-processed images containing 2,352 images. The aims of this research are to show that using a synthetic ‘Signal for Help’ dataset improves model performance, and using deep learning is effective in ‘Signal for Help’ hand gesture classification. The results in this research show that using a synthetic ‘Signal for Help’ dataset improves model performance and is effective for ‘Signal for Help’ hand gesture classification.