Enhancing In-Cabin Video Experience Using Driver Monitoring IR Camera

Enhancing In-Cabin Video Experience Using Driver Monitoring IR Camera | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Enhancing In-Cabin Video Experience Using Driver Monitoring IR Camera Mohamed SAEED HAMMAD, Walid Al-Atabany This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7059997/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Safety regulations such as Euro NCAP and the General Safety Regulation (GSR) mandate the inclusion of in-cabin infrared (IR) cameras in every new car for enhanced safety and monitoring. IR cameras are highly effective in detecting faces and extracting facial features, making them an excellent choice for driver monitoring systems. This paper explores the use of these pre-installed IR cameras beyond safety applications, specifically for real-time video conferencing. Leveraging artificial intelligence (AI) techniques, we propose a framework that enhances IR-based video communication while maintaining privacy and robustness under various lighting conditions. The system integrates the Mediapipe framework for face detection, tracking, and segmentation, combined with AI-driven image enhancement techniques to improve the visual quality of IR-based video feeds. To assess the effectiveness of our approach, we evaluate multiple qualitative and quantitative criteria, including sharpness, noise levels, facial feature clarity, edge artifacts, and video smoothness. Our results demonstrate that IR cameras, when enhanced with AI techniques, can serve as a viable alternative to traditional RGB-based in-cabin communication systems, offering a cost-effective and privacy-preserving solution. Infrared imagery Deep learning Face detection In-cabin video Driver monitoring AI-enhanced communication Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7059997","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":484776478,"identity":"acb32bf8-4c8e-4895-af75-435cbdb2c5a4","order_by":0,"name":"Mohamed SAEED HAMMAD","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYBADxn4wxUaKlpkNJGvZcIBYLbrtDcwfflTYyG6+3WPA8KHsMAM//wL8WszOHGCT7DmTZrztzhkDxhnnDjNIznhAQMuNBDYG3rbDidtu5BgwAxkMBjcOENTC/PHvv/+Jm2cAtfwFarEnQguDNG/DgcQNEkAtjCBb+BsI+eVgm7TMsWTjGTfSCg72nEvnkbiBXweD2fHmwx/f1NjJ9s9I3vjgR5m1HH8/AYcBYwThDpBaHgaJBEJaMAA/QVtGwSgYBaNghAEA2kxItureDYwAAAAASUVORK5CYII=","orcid":"","institution":"Nile University","correspondingAuthor":true,"prefix":"","firstName":"Mohamed","middleName":"SAEED","lastName":"HAMMAD","suffix":""},{"id":484776479,"identity":"89c71318-d54d-4b62-877d-9252247194a5","order_by":1,"name":"Walid Al-Atabany","email":"","orcid":"","institution":"Nile University","correspondingAuthor":false,"prefix":"","firstName":"Walid","middleName":"","lastName":"Al-Atabany","suffix":""}],"badges":[],"createdAt":"2025-07-06 22:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7059997/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7059997/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87529681,"identity":"9dc02c7d-3064-4731-a48a-08b7c167e6f3","added_by":"auto","created_at":"2025-07-24 21:16:31","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":507553,"visible":true,"origin":"","legend":"","description":"","filename":"EnhancingInCabinVideoExperienceUsingDriverMonitoringIRCameraV1.1.0.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7059997/v1_covered_2c8cb946-9c0f-4bb6-9774-5650217ab4fa.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Enhancing In-Cabin Video Experience Using Driver Monitoring IR Camera","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Infrared imagery, Deep learning, Face detection, In-cabin video, Driver monitoring, AI-enhanced communication","lastPublishedDoi":"10.21203/rs.3.rs-7059997/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7059997/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":" \nSafety regulations such as Euro NCAP and the General Safety Regulation (GSR) mandate the inclusion of in-cabin infrared (IR) cameras in every new car for enhanced safety and monitoring. IR cameras are highly effective in detecting faces and extracting facial features, making them an excellent choice for driver monitoring systems. This paper explores the use of these pre-installed IR cameras beyond safety applications, specifically for real-time video conferencing. Leveraging artificial intelligence (AI) techniques, we propose a framework that enhances IR-based video communication while maintaining privacy and robustness under various lighting conditions. The system integrates the Mediapipe framework for face detection, tracking, and segmentation, combined with AI-driven image enhancement techniques to improve the visual quality of IR-based video feeds. To assess the effectiveness of our approach, we evaluate multiple qualitative and quantitative criteria, including sharpness, noise levels, facial feature clarity, edge artifacts, and video smoothness. 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