GesSure: A Robust Face-Authentic Enabled Dynamic Gesture Recognition GUI Application

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Existing gesturerecognition systems do not possess user authentication, making them unreliable. Static gestures in current gesture-recognition technology introduce long adaptation periods and reduce user compatibility. Our technology places a strong emphasis on user recognition and safety. We use meaningful and relevant gestures for task operation, resulting in a better user experience. This paper aims to design a robust, faceverification-enabled gesture recognition system that utilizes a graphical user interface and primarily focuses on security through user recognition and authorization. The face model uses MTCNN and FaceNet to verify the user, and our LSTM-CNN architecture for gesture recognition, achieving an accuracy of 95% with five classes of gestures. The prototype developed through our research has successfully executed context-dependent tasks like save, print, control video-player operations and exit, and context-free operating system tasks like sleep, shut-down, and unlock intuitively. Our application and dataset are available as open source"> <meta name="keywords" content="Gesture Recognition, Human Computer Interaction, Face Authentication, CNN-LSTM, MediaPipe"/>   <meta name="dc.title" content="GesSure: A Robust Face-Authentic Enabled Dynamic Gesture Recognition GUI Application "> <meta name="citation_authors" content="Ankit Jha"> <meta name="citation_authors" content="Pratham G. Shenwai"> <meta name="citation_authors" content="Ayush Batra"> <meta name="citation_authors" content="Siddharth Kotian"> <meta name="citation_authors" content="Piyush Modi"> <meta name="dc.type" content="Article"> <meta name="dc.source" content="International Journal on Cybernetics & Informatics (IJCI) Vol. 11, No.04"> <meta name="dc.date" content="2022/08/27"> <meta name="dc.identifier" content="10.5121/ijci.2022.110402"> <meta name="dc.publisher" content="AIRCC Publishing Corporation"> <meta name="dc.rights" content="http://creativecommons.org/licenses/by/3.0/"> <meta name="dc.format" content="application/pdf"> <meta name="dc.language" content="en"> <meta name="dc.description" content="Using physical interactive devices like mouse and keyboards hinders naturalistic human-machine interaction and increases the probability of surface contact during a pandemic. Existing gesturerecognition systems do not possess user authentication, making them unreliable. Static gestures in current gesture-recognition technology introduce long adaptation periods and reduce user compatibility. Our technology places a strong emphasis on user recognition and safety. We use meaningful and relevant gestures for task operation, resulting in a better user experience. This paper aims to design a robust, faceverification-enabled gesture recognition system that utilizes a graphical user interface and primarily focuses on security through user recognition and authorization. The face model uses MTCNN and FaceNet to verify the user, and our LSTM-CNN architecture for gesture recognition, achieving an accuracy of 95% with five classes of gestures. The prototype developed through our research has successfully executed context-dependent tasks like save, print, control video-player operations and exit, and context-free operating system tasks like sleep, shut-down, and unlock intuitively. Our application and dataset are available as open source. "/> <meta name="dc.subject" content="Gesture Recognition"> <meta name="dc.subject" content=" Human Computer Interaction"> <meta name="dc.subject" content=" Face Authentication"> <meta name="dc.subject" content=" CNN-LSTM"> <meta name="dc.subject" content=" MediaPipe">   <meta name="prism.publicationName" content="International Journal on Cybernetics & Informatics (IJCI) "> <meta name="prism.publicationDate" content="2022/08/27"> <meta name="prism.volume" content="11"> <meta name="prism.number" content="4"> <meta name="prism.section" content="Article"> <meta name="prism.startingPage" content="19">   <meta name="citation_journal_title" content="International Journal on Cybernetics & Informatics (IJCI)"> <meta name="citation_publisher" content="AIRCC Publishing Corporation"> <meta name="citation_authors" content="Ankit Jha, Ishita, Pratham G. Shenwai, Ayush Batra,Siddharth Kotian and Piyush Modi "> <meta name="citation_title" content="GesSure: A Robust Face-Authentic Enabled Dynamic Gesture Recognition GUI Application"> <meta name="citation_online_date" content="2022/08/27"> <meta name="citation_issue" content="11"> <meta name="citation_firstpage" content="19"> <meta name="citation_authors" content="Ankit Jha"> <meta name="citation_authors" content="Pratham G. Shenwai"> <meta name="citation_authors" content="Ayush Batra"> <meta name="citation_authors" content="Siddharth Kotian"> <meta name="citation_authors" content="Piyush Modi"> <meta name="citation_doi" content="10.5121/ijci.2022.110402"> <meta name="citation_abstract_html_url" content="https://ijcionline.com/abstract/11422ijci02"> <meta name="citation_pdf_url" content="https://ijcionline.com/paper/11/11422ijci02.pdf">   <meta property="og:site_name" content="AIRCC" /> <meta property="og:type" content="article" /> <meta property="og:url" content="https://ijcionline.com/abstract/11422ijci02"> <meta property="og:title" content="GesSure: A Robust Face-Authentic Enabled Dynamic Gesture Recognition GUI Application "> <meta property="og:description" content="Using physical interactive devices like mouse and keyboards hinders naturalistic human-machine interaction and increases the probability of surface contact during a pandemic. Existing gesturerecognition systems do not possess user authentication, making them unreliable. Static gestures in current gesture-recognition technology introduce long adaptation periods and reduce user compatibility. Our technology places a strong emphasis on user recognition and safety. We use meaningful and relevant gestures for task operation, resulting in a better user experience. This paper aims to design a robust, faceverification-enabled gesture recognition system that utilizes a graphical user interface and primarily focuses on security through user recognition and authorization. The face model uses MTCNN and FaceNet to verify the user, and our LSTM-CNN architecture for gesture recognition, achieving an accuracy of 95% with five classes of gestures. The prototype developed through our research has successfully executed context-dependent tasks like save, print, control video-player operations and exit, and context-free operating system tasks like sleep, shut-down, and unlock intuitively. Our application and dataset are available as open source. 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Shenwai, Ayush Batra, Siddharth Kotian and Piyush Modi, Manipal Institute of Technology, MAHE, India </p> </div> </div>   <div class="card"> <h5 id="about" class="brown-text text-darken-2 text-center" style="padding-bottom:0px">Abstract</h5>  <div class="card-content"> <p class="left-text" style="text-align:justify"> Using physical interactive devices like mouse and keyboards hinders naturalistic human-machine interaction and increases the probability of surface contact during a pandemic. Existing gesturerecognition systems do not possess user authentication, making them unreliable. Static gestures in current gesture-recognition technology introduce long adaptation periods and reduce user compatibility. Our technology places a strong emphasis on user recognition and safety. We use meaningful and relevant gestures for task operation, resulting in a better user experience. This paper aims to design a robust, faceverification-enabled gesture recognition system that utilizes a graphical user interface and primarily focuses on security through user recognition and authorization. The face model uses MTCNN and FaceNet to verify the user, and our LSTM-CNN architecture for gesture recognition, achieving an accuracy of 95% with five classes of gestures. The prototype developed through our research has successfully executed context-dependent tasks like save, print, control video-player operations and exit, and context-free operating system tasks like sleep, shut-down, and unlock intuitively. Our application and dataset are available as open source. </p> </div> </div> <div class="card"> <h5 id="about" class="brown-text text-darken-2 text-center" style="padding-bottom:0px">Keywords</h5>  <div class="card-content"> <p class="left-text" style="text-align:justify"> Gesture Recognition, Human Computer Interaction, Face Authentication, CNN-LSTM, MediaPipe. </p> </div> </div> <div class="card-content"> <a href="/paper/11/11422ijci02.pdf" target="_blank" class="btn btn-small lighten-2 cyan lig">Full Text</a>  <a href="/volume11" target="_blank" class="btn btn-small lighten-2 cyan lig">Volume 11</a> </div> </div>  <div id="side-bar" class="col s12 m3"> <div id="section-main"> <br> <br> <div class="card side cyan lighten-2"> <div class="card-content"> <ul> <li class="ax waves-effect waves-light"> <a class="white-text" href="/editorial" > <i class="material-icons left">account_circle</i>Editorial Board</a> <br> </li> <br> <br> <div class="divider"></div> <br> <li class="ax waves-effect waves-light"> <a class="white-text" href="/mostcitedarticels" > <i class="material-icons left">book</i>Most Cited Articels </a> <br> </li> <br> <br> <div class="divider"></div> <br> <li class="ax waves-effect waves-light"> <a class="white-text" href="/indexing" > <i class="material-icons left">list</i>Indexing </a> <br> </li> <br> <br> <div class="divider"></div> <br> <li class="ax waves-effect waves-light"> <a class="white-text" href="/faq" > <i class="material-icons left">help</i>FAQ </a> <br> </li> <br> <br> <div class="divider"></div> <br> </div> </div> </div> </div> </div> </div> </div> </section> <br> <br> <br> <br> <div id="txtcnt"></div>  <footer class="page-footer cyan lighten-3"> <div class="nav-wrapper"> <div class="container"> <ul> <li> <a target="_blank" href="http://airccse.org/"> <img src="/img/since2008.png" alt="since2008"></a> </li> </ul> <h6> Free Open Access Conference Proceedings <br> Computer Science & Engineering - Information Technology - Information Systems</h6> </div> <div class="footer-m col m3 s12 offset-m1"> </div> <div class="social col m3 offset-m1 s12"> </div> </div> </div> <div class="col s12 m10 offset-m1"> <div class="grey darken-3 center-align"> <small class="white-text">Designed and Developed by NNN Team</small> </div> </div> </footer> </body>  <script type="text/javascript" src="https://code.jquery.com/jquery-3.2.1.min.js"></script> <script type="text/javascript" src="/js/materialize.min.js"></script> <script src="/js/search.js"></script> <script src="/js/scrolltop.js"></script> <script src="/js/popup.js"></script> <script src="/js/main.jquery.js"></script> </html>

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GesSure: A Robust Face-Authentic Enabled Dynamic Gesture Recognition GUI Application