Personalized and dynamic rear-view mirror adjustment and profiling with voice signature

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Huseyin Karacali
Nevzat Donum
Efecan Cebel

Abstract

This paper introduces a novel automated system designed for adjusting automobile rear-view mirrors intelligently by utilizing head pose orientation. In today's increasingly personalized car interiors, ensuring the correct alignment of the rear-view mirror based on the driver's head orientation significantly enhances both safety and driving comfort. Manual adjustment of rear-view mirrors can result in issues such as improper angles and driver distractions. This study aims to automate the rear-view mirror adjustment process by accurately detecting the driver's head position and orientation, thereby mitigating these challenges. The system incorporates a camera within the vehicle's cockpit to track the driver. Raw data captured by the camera undergoes processing using the Perspective-n-Point (PnP) algorithm to determine the driver's head position and orientation. The computed positional information is then employed to precisely align the rear-view mirror, optimizing the field of view and eliminating blind spots. Within a brief timeframe, the system establishes the most suitable mirror settings for any driver. Moreover, it dynamically adapts to changes in the driver's posture during driving, ensuring consistently optimal visibility. Additionally, faster and more comfortable use of this in-car smart system is aimed with voice identification technology. Mirror angle values are kept in memory and can be applied instantly at the driver's request, with driver profiles created with voice identifications. Consequently, this research proposes an innovative application that contributes to the integration and personalization of smart technologies, potentially becoming part of forthcoming automotive cockpit designs.

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How to Cite
Karacali, H., Donum, N., & Cebel, E. (2023). Personalized and dynamic rear-view mirror adjustment and profiling with voice signature. The European Journal of Research and Development, 3(4), 390–413. https://doi.org/10.56038/ejrnd.v3i4.278
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