Hybrid Eye-Tracking System for Cursor Control: A Kalman Filter and Exponential Moving Average-Based Approach for Robust Face Tracking

Hybrid Eye-Tracking System for Cursor Control: A Kalman Filter and Exponential Moving Average-Based Approach for Robust Face Tracking | 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 Hybrid Eye-Tracking System for Cursor Control: A Kalman Filter and Exponential Moving Average-Based Approach for Robust Face Tracking S BALAJI, DR POTHULA SUJATHA This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6541901/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 Precise and efficient real-time eye-tracking is essential for hands-free cursor control, aiding accessibility and human-computer interaction. Traditional eye-tracking methods often suffer from latency, noise interference, and inaccurate tracking, limiting their practical usability. To address these challenges, we propose a Hybrid Eye-Tracking System (HETS) that integrates MediaPipe, Dlib, Kalman Filtering, and Exponential Moving Average (EMA) smoothing to enhance tracking accuracy and responsiveness. Our approach combines Kalman Filter-based motion prediction with adaptive noise reduction using EMA, reducing jitter and improving cursor stability. Furthermore, we introduce a multi-modal facial landmark detection strategy by fusing deep-learning-based MediaPipe Face Mesh with Dlib’s shape predictor, ensuring robust and adaptive tracking across diverse environments. The system operates in real-time with a lightweight architecture, making it suitable for assistive technology and hands-free computing applications. Experimental results demonstrate superior tracking accuracy and smoothness compared to conventional methods. For further details and access to the implementation, please visit our repository: https://github.com/balajisaba/hybrid-gazing Eye-tracking Cursor control Kalman Filter Exponential Moving Average Facial landmark detection Real-time tracking Human-computer interaction 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6541901","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":451702851,"identity":"86c0a7c3-caa6-43c6-a00f-42fc87040ca0","order_by":0,"name":"S BALAJI","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYDACCQbGAww8EmDGAyCfh48ILQwwLcwGIC1sxGmBMNgkQDRBLfKzmx8c+CFjYc8/u/lZ5dccOxk2BuaHDz7m4NZicOeYwcEeHonEGXeOmd2W3ZYMdBibseHMbXi0SCQYHODhkUhguJFgdltyGzNQCw+bNC8eLfIz0j8c/MMjYS9/I/1bseS2esJaGG7kGBwG2sK44UaOGePHbYcJazG4c6bgsAzQLxvvnCmWZtx2nIeNmYBf5Ge3b3z4tqfOXu52+8aPP7dV2/OzNwNDDJ/DQICxB0Iz84BJAqoh4AdU6w+iVI+CUTAKRsFIAwAnUU0BzCbhVQAAAABJRU5ErkJggg==","orcid":"","institution":"Pondicherry University","correspondingAuthor":true,"prefix":"","firstName":"S","middleName":"","lastName":"BALAJI","suffix":""},{"id":451702852,"identity":"a5d6b186-fd2a-48c8-96e9-00f762d31deb","order_by":1,"name":"DR POTHULA SUJATHA","email":"","orcid":"","institution":"Pondicherry University","correspondingAuthor":false,"prefix":"DR","firstName":"POTHULA","middleName":"","lastName":"SUJATHA","suffix":""}],"badges":[],"createdAt":"2025-04-27 17:53:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6541901/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6541901/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90903083,"identity":"5e753847-2bd4-484e-828e-158a14aa8e63","added_by":"auto","created_at":"2025-09-09 12:47:09","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":866019,"visible":true,"origin":"","legend":"","description":"","filename":"Hybridgazing.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6541901/v1_covered_7f203d8d-92d5-4f02-bbe1-39d282656b89.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eHybrid Eye-Tracking System for Cursor Control: A Kalman Filter and Exponential Moving Average-Based Approach for Robust Face Tracking\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Eye-tracking, Cursor control, Kalman Filter, Exponential Moving Average, Facial landmark detection, Real-time tracking, Human-computer interaction","lastPublishedDoi":"10.21203/rs.3.rs-6541901/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6541901/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePrecise and efficient real-time eye-tracking is essential for hands-free cursor control, aiding accessibility and human-computer interaction. 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