Real time hand gesture detection by using convolutional neural network for in-vehicle infortainment systems

Nowadays, <span>a variety of technologies on autonomous vehicles have been extensively developed, including in-vehicle infotainment (IVI). It have been noted as one of the key services in the automobile industry. In the near future, people will be able to watch some virtual reality (VR) movies through the streaming service provided in the vehicle. However, a person sometime not tend to be joy while watching espcially when the remote controller or audio sensory controller lack of battery or too far from IVI panel. Thus, the purpose of this research is to design a scheme of real time hand gesture detection for in-vehicle infotainment system, in order to create human computer experience. In this research, the image of human palm hand will be taken by using camera for recognize the hand gesture action. This proposed scheme will recognize human gesture and convert to be computer intruction, that can be understood by IVI device. As a result, it show our proposed scheme can be the most consistent in term of accuracy and loss compared to others method. Overall, this research represents a significant step toward improving better user experience. Furthermore, the proposed scheme is anticipated to contribute significantly to the IVI field, benefiting both academia and societal outcomes.</span>

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Publication Details

Journal
International Journal of Informatics and Communication Technology (IJ-ICT)
Published
2024-12-22
DOI
https://doi.org/10.11591/ijict.v14i1.pp42-49
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
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article

Real time hand gesture detection by using convolutional neural network for in-vehicle infortainment systems

Najwan Khambari, Nur Raidah Rahim, Raja Rina Raja Ikram, Mohd Sanusi Azmi et al.
International Journal of Informatics and Communication Technology (IJ-ICT)
Hand Gesture Recognition Systems
article

Real time hand gesture detection by using convolutional neural network for in-vehicle infortainment systems

Najwan Khambari, Nur Raidah Rahim, Raja Rina Raja Ikram, Mohd Sanusi Azmi, Yus Sholva, Siti Azirah Asmai, Wan Mohd Yaakob Wan Bejuri
article en

Abstract

Nowadays, <span>a variety of technologies on autonomous vehicles have been extensively developed, including in-vehicle infotainment (IVI). It have been noted as one of the key services in the automobile industry. In the near future, people will be able to watch some virtual reality (VR) movies through the streaming service provided in the vehicle. However, a person sometime not tend to be joy while watching espcially when the remote controller or audio sensory controller lack of battery or too far from IVI panel. Thus, the purpose of this research is to design a scheme of real time hand gesture detection for in-vehicle infotainment system, in order to create human computer experience. In this research, the image of human palm hand will be taken by using camera for recognize the hand gesture action. This proposed scheme will recognize human gesture and convert to be computer intruction, that can be understood by IVI device. As a result, it show our proposed scheme can be the most consistent in term of accuracy and loss compared to others method. Overall, this research represents a significant step toward improving better user experience. Furthermore, the proposed scheme is anticipated to contribute significantly to the IVI field, benefiting both academia and societal outcomes.</span>

International Journal of Informatics and Communication Technology (IJ-ICT)Vol. 14(1)
Tanjungpura University (ID), Technical University of Malaysia Malacca (MY)
Openalex Percentile: Top 76%
Hand Gesture Recognition Systems
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