Russian Sign Language Dactyl Recognition
Ilya Makarov, Nikolay Veldyaykin, Maxim Chertkov, Aleksei Pokoev · 2019
In this paper, we compare several real-time sign language dactyl recognition systems and present a new model based on deep convolutional neural networks. These systems are able to recognize Russian alphabet letters presented as static signs in Russian Sign language used by people from deaf community. In such an approach, we recognize words from Russian natural language presented by consequent hand gestures of each letter. We evaluate our approach on Russian (RSL) sign language, for which we collect our own dataset and evaluate dactyl recognition.