Automatic Seat Adjustment using Face Recognition

Vamsi, Malneedi; Soman, K P; Guruvayurappan, K.

doi:10.1109/icict48043.2020.9112538

Cited by 8 publications

(2 citation statements)

References 10 publications

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“…A perfect seat position setting is one of the preferred factors for a safe and comfortable ride [28]. In recent years, facial recognition-based seat adjustment techniques [29], and mirror adjustment through driver's pupil [30] were studied. From the participants' opinions, it is also highly desirable to include adjusting the seat position and mirror according to the next expected driver.…”

Section: Discussionmentioning

confidence: 99%

Prediction of attitudes towards human-centred cognitive vehicles aware of their users' routines and preferences

Patel

Ferreira

Monteiro

et al. 2021

2021 IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI)

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Advances in the automotive industry are changing the relationship between cars and drivers. Advanced driver assistant systems, such as navigation systems, advanced cruise control, collision avoidance systems, and other safety systems, are now common and assist the driver in controlling the car. Smart key fobs have made getting in and starting the car almost effortless: the fob can be left in the pocket and the doors will unlock when a driver/user approaches the car and simply touches the door handle. This is a level of personalization and convenience that is almost standard today. The research presented here brings a new perspective on personalization and driver assistance systems. An online survey was conducted, which aimed to gather public opinion on the usefulness of endowing future (semi-)autonomous cars with social and cognitive behavior, such as the ability to learn drivers' routines and preferences in order to make decisions and perform actions in preparation for the next trip and to manage comfort within the cockpit without being commanded to do so. After filtering, the study included 657 respondents from 93 nations. The results demonstrate a favorable opinion towards such human-centered cognitive vehicles and could be helpful for designers in the automotive industry and other related stakeholders in the development of future cognitive vehicles.

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Section: Discussionmentioning

confidence: 99%

Prediction of attitudes towards human-centred cognitive vehicles aware of their users' routines and preferences

Patel

Ferreira

Monteiro

et al. 2021

2021 IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI)

View full text Add to dashboard Cite

show abstract

“…To overcome these challenges, efforts are being made in the automotive domain to develop more user-friendly and automated profile selection systems. Systems developed to automate the process of seat adjustment using facial recognition are examples of such studies [1]. In-vehicle customizable systems can also be controlled by voice recognition technologies in addition to facial recognition technology.…”

Section: Introductionmentioning

confidence: 99%

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

Karacali,

Donum,

Cebel

2023

EJRnD

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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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Artificial Intelligence-based Vehicle In-Cabin Occupant Detection and Classification System

Tamizharasan¹,

Lakshmikanthan²

2022

Lecture Notes in Networks and Systems

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Automatic Seat Adjustment using Face Recognition

Cited by 8 publications

References 10 publications

Prediction of attitudes towards human-centred cognitive vehicles aware of their users' routines and preferences

Prediction of attitudes towards human-centred cognitive vehicles aware of their users' routines and preferences

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

Artificial Intelligence-based Vehicle In-Cabin Occupant Detection and Classification System

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