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A Dynamic Gesture Recognition Interface for Smart Home Control based on Croatian Sign Language (CROSBI ID 277317)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Kraljević, Luka ; Russo, Mladen ; Pauković, Matija ; Šarić, Matko A Dynamic Gesture Recognition Interface for Smart Home Control based on Croatian Sign Language // Applied sciences (Basel), 10 (2020), 7; 2300, 16. doi: 10.3390/app10072300

Podaci o odgovornosti

Kraljević, Luka ; Russo, Mladen ; Pauković, Matija ; Šarić, Matko

engleski

A Dynamic Gesture Recognition Interface for Smart Home Control based on Croatian Sign Language

Deaf and hard-of-hearing people are facing many challenges in everyday life. Their communication is based on the use of a sign language, and the ability of the cultural/social environment to fully understand such a language defines whether or not it will be accessible for them. Technology is a key factor that has the potential to provide solutions to achieve a higher accessibility and therefore improve the quality of life of deaf and hard-of- hearing people. In this paper, we introduce a smart home automatization system specifically designed to provide real- time sign language recognition. The contribution of this paper implies several elements. Novel hierarchical architecture is presented, including resource-and-time- aware modules—a wake-up module and high-performance sign recognition module based on the Conv3D network. To achieve high-performance classification, multi-modal fusion of RGB and depth modality was used with the temporal alignment. Then, a small Croatian sign language database containing 25 different language signs for the use in smart home environment was created in collaboration with the deaf community. The system was deployed on a Nvidia Jetson TX2 embedded system with StereoLabs ZED M stereo camera for online testing. Obtained results demonstrate that the proposed practical solution is a viable approach for real-time smart home control.

sign language ; multimodal gesture recognition ; home automatization ; 3D convolution

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Podaci o izdanju

10 (7)

2020.

2300

16

objavljeno

2076-3417

10.3390/app10072300

Povezanost rada

Informacijske i komunikacijske znanosti, Računarstvo

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