Feature Extraction with Video Summarization of Dynamic Gestures for Peruvian Sign Language Recognition

Neyra-Gutierrez A.; Shiguihara-Juarez P. · Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020 (2020) · DOI: 10.1109/intercon50315.2020.9220243

Resumen

In peruvian sign language (PSL), recognition of static gestures has been proposed earlier. However, to state a conversation using sign language, it is also necessary to employ dynamic gestures. We propose a method to extract a feature vector for dynamic gestures of PSL. We collect a dataset with 288 video sequences of words related to dynamic gestures and we state a workflow to process the keypoints of the hands, obtaining a feature vector for each video sequence with the support of a video summarization technique. We employ 9 neural networks to test the method, achieving an average accuracy ranging from 80% and 90%, using 10 fold cross-validation.

Instituciones: Universidad Peruana de Ciencias Aplicadas