A deep hybrid model for human-computer interaction using dynamic hand gesture recognition

• Autorzy: Ramalingam Brindha , Angappan Geetha

Identyfikatory

DOI

10.24423/cames.559

• Języki publikacji: EN

Abstrakty

EN

Dynamic hand gestures attract great interest and are utilized in different fields. Amongthese, man-machine interaction is an interesting area that makes use of the hand to providea natural way of interaction between them. A dynamic hand gesture recognition system isproposed in this paper, which helps to perform control operations in applications such asmusic players, video games, etc. The key motivation of this research is to provide a simple, touch-free system for effortless and faster human-computer interaction (HCI). As thisproposed model employs dynamic hand gestures, HCI is achieved by building a modelwith a convolutional neural network (CNN) and long short-term memory (LSTM) net-works. CNN helps in extracting important features from the images and LSTM helpsto extract the motion information between the frames. Various models are constructedby differing the LSTM and CNN layers. The proposed system is tested on an existing EgoGesture dataset that has several classes of gestures from which the dynamic gesturesare utilized. This dataset is used as it has more data with a complex background, actionsperformed with varying speeds, lighting conditions, etc. This proposed hand gesture recognition system attained an accuracy of 93%, which is better than other existing systemssubject to certain limitations.

Słowa kluczowe

EN

dynamic hand gesture; human-computer interaction; long short-term memory; convolutional neural network

PL

dynamiczny gest ręki; interakcja człowiek-komputer; pamięć krótkotrwała; konwolucyjna sieć neuronowa

• Wydawca: Instytut Podstawowych Problemów Techniki PAN
• Czasopismo: Computer Assisted Methods in Engineering and Science
• Rocznik: 2023
• Tom: Vol. 30, no. 3
• Strony: 263--276
• Opis fizyczny: Bibliogr. 26 poz., il., tab., wykr.

Twórcy

autor

Ramalingam Brindha

• Computer Science and Engineering, Annamalai University, Annamalai Nagar,Chidambaram, India

autor

Angappan Geetha

• Computer Science and Engineering, Annamalai University, Annamalai Nagar,Chidambaram, India

Bibliografia

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