Real time hand gesture detection by using convolutional neural network for in-vehicle infortainment systems - Yaakob Wan Bejuri, Wan Mohd; Asmai, Siti Azira; Ikram, Raja Rina Raja; Rahim, Nur Raidah; Khambari, Najwan; Azmi, Mohd Sanusi; Sholva, Yus (International Journal of Informatics and Communication Technology (IJ-ICT), 2025)
Nowadays, 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.