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window.loswp.shouldShowBulkDownload = true; window.loswp.showSignupCaptcha = false window.loswp.willEdgeCache = false; window.loswp.work = {"work":{"id":111609796,"created_at":"2023-12-16T23:55:54.710-08:00","from_world_paper_id":245980093,"updated_at":"2024-11-26T14:54:34.698-08:00","_data":{"publisher":"SCITEPRESS - Science and and Technology Publications","grobid_abstract":"In this paper we propose a recognition technique of 3D dynamic gesture for human robot interaction (HRI) based on depth information provided by Kinect sensor. The body is tracked using the skeleton algorithm provided by the Kinect SDK. The main idea of this work is to compute the angles of the upper body joints which are active when executing gesture. The variation of these angles are used as inputs of Hidden Markov Models (HMM) in order to recognize the dynamic gestures. Results demonstrate the robustness of our method against environmental conditions such as illumination changes and scene complexity due to using depth information only.","publication_date":"2015,,","publication_name":"Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics","grobid_abstract_attachment_id":"109098734"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"A Depth-based Approach for 3D Dynamic Gesture Recognition","broadcastable":false,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [263837202]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "full_page_mobile_sutd_modal"; window.loswp.useOptimizedScribd4genScript = false; window.loswp.appleClientId = 'edu.academia.applesignon';</script><script 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20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">A Depth-based Approach for 3D Dynamic Gesture Recognition</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="263837202" href="https://gadz.academia.edu/FakhreddineAbabsa"><img alt="Profile image of Fakhreddine Ababsa" class="ds-work-card--author-avatar" src="https://0.academia-photos.com/263837202/115339392/104625007/s65_fakhreddine.ababsa.png" />Fakhreddine Ababsa</a></div><div class="ds-work-card--detail"><p class="ds-work-card--detail ds2-5-body-sm">2015, Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics</p></div><div 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data-login_uri="https://www.academia.edu/registrations/google_one_tap" data-moment_callback="onGoogleOneTapEvent" id="g_id_onload"></div><div class="ds-top-related-works--grid-container"><div class="ds-related-content--container ds-top-related-works--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="0" data-entity-id="19597868" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/19597868/HAGR_D_A_Novel_Approach_for_Gesture_Recognition_with_Depth_Maps">HAGR-D: A Novel Approach for Gesture Recognition with Depth Maps</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="5151406" href="https://upe.academia.edu/DiegoThuran">Diego Thuran</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="26589264" href="https://independent.academia.edu/DiegoSilva82">Diego Silva</a></div><p class="ds-related-work--abstract ds2-5-body-sm">The hand is an important part of the body used to express information through gestures, and its movements can be used in dynamic gesture recognition systems based on computer vision with practical applications, such as medical, games and sign language. Although depth sensors have led to great progress in gesture recognition, hand gesture recognition still is an open problem because of its complexity, which is due to the large number of small articulations in a hand. This paper proposes a novel approach for hand gesture recognition with depth maps generated by the Microsoft Kinect Sensor (Microsoft, Redmond, WA, USA) using a variation of the CIPBR (convex invariant position based on RANSAC) algorithm and a hybrid classifier composed of dynamic time warping (DTW) and Hidden Markov models (HMM), called the hybrid approach for gesture recognition with depth maps (HAGR-D). 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href="https://www.academia.edu/19597868/HAGR_D_A_Novel_Approach_for_Gesture_Recognition_with_Depth_Maps"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="82083933" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/82083933/Gesture_recognition_using_Microsoft_Kinect_">Gesture recognition using Microsoft Kinect®</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="143504034" href="https://independent.academia.edu/BiswasKanad">Kanad Biswas</a></div><p class="ds-related-work--metadata ds2-5-body-xs">The 5th International Conference on Automation, Robotics and Applications, 2011</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Gesture recognition using Microsoft Kinect®","attachmentId":87902687,"attachmentType":"pdf","work_url":"https://www.academia.edu/82083933/Gesture_recognition_using_Microsoft_Kinect_","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/82083933/Gesture_recognition_using_Microsoft_Kinect_"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="112075127" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/112075127/Recognition_of_Human_Gestures_Represented_by_Depth_Camera_Motion_Sequences">Recognition of Human Gestures Represented by Depth Camera Motion Sequences</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="284702862" href="https://independent.academia.edu/HenrykJosinski">Henryk Josinski</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Studies in Computational Intelligence, 2015</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Recognition of Human Gestures Represented by Depth Camera Motion Sequences","attachmentId":109418412,"attachmentType":"pdf","work_url":"https://www.academia.edu/112075127/Recognition_of_Human_Gestures_Represented_by_Depth_Camera_Motion_Sequences","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/112075127/Recognition_of_Human_Gestures_Represented_by_Depth_Camera_Motion_Sequences"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="98060536" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/98060536/Gesture_recognition_using_a_depth_sensor_and_machine_learning_techniques">Gesture recognition using a depth sensor and machine learning techniques</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="260430642" href="https://independent.academia.edu/MarinaRipoll3">Marina Ripoll</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2017</p><p class="ds-related-work--abstract ds2-5-body-sm">Advances in depth sensing provide great opportunities for the development of new methods for human computer interactivity. 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Finally, it is given an overview of the challenges i...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Gesture recognition using a depth sensor and machine learning techniques","attachmentId":99515301,"attachmentType":"pdf","work_url":"https://www.academia.edu/98060536/Gesture_recognition_using_a_depth_sensor_and_machine_learning_techniques","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/98060536/Gesture_recognition_using_a_depth_sensor_and_machine_learning_techniques"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="77653522" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/77653522/Recognition_of_Symbolic_Gestures_Using_Depth_Information">Recognition of Symbolic Gestures Using Depth Information</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="44127975" href="https://independent.academia.edu/HasanulKabir1">Hasanul Kabir</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Advances in Human-Computer Interaction, 2018</p><p class="ds-related-work--abstract ds2-5-body-sm">Symbolic gestures are the hand postures with some conventionalized meanings. They are static gestures that one can perform in a very complex environment containing variations in rotation and scale without using voice. The gestures may be produced in different illumination conditions or occluding background scenarios. Any hand gesture recognition system should find enough discriminative features, such as hand-finger contextual information. However, in existing approaches, depth information of hand fingers that represents finger shapes is utilized in limited capacity to extract discriminative features of fingers. Nevertheless, if we consider finger bending information (i.e., a finger that overlaps palm), extracted from depth map, and use them as local features, static gestures varying ever so slightly can become distinguishable. Our work here corroborated this idea and we have generated depth silhouettes with variation in contrast to achieve more discriminative keypoints. This approac...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Recognition of Symbolic Gestures Using Depth Information","attachmentId":84965342,"attachmentType":"pdf","work_url":"https://www.academia.edu/77653522/Recognition_of_Symbolic_Gestures_Using_Depth_Information","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/77653522/Recognition_of_Symbolic_Gestures_Using_Depth_Information"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="55021729" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/55021729/The_Issues_of_3D_Hand_Gesture_and_Posture_Recognition_Using_the_Kinect">The Issues of 3D Hand Gesture and Posture Recognition Using the Kinect</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="49887273" href="https://univ-ubs.academia.edu/Poirier">Franck Poirier</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Lecture Notes in Computer Science, 2014</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"The Issues of 3D Hand Gesture and Posture Recognition Using the Kinect","attachmentId":71096610,"attachmentType":"pdf","work_url":"https://www.academia.edu/55021729/The_Issues_of_3D_Hand_Gesture_and_Posture_Recognition_Using_the_Kinect","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/55021729/The_Issues_of_3D_Hand_Gesture_and_Posture_Recognition_Using_the_Kinect"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="91084652" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/91084652/Real_Time_3D_Hand_Gesture_Detection_from_Depth_Images">Real-Time 3D Hand Gesture Detection from Depth Images</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="246067287" href="https://independent.academia.edu/YuXiao83">Yu Xiao</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Advanced Materials Research, 2013</p><p class="ds-related-work--abstract ds2-5-body-sm">In this paper, we describe an real-time algorithm to detect 3D hand gestures from depth images. 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Experiments on Microsoft Kinect for Xbox captured sequences show the effectiveness and efficiency of our system.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Real-Time 3D Hand Gesture Detection from Depth Images","attachmentId":94471246,"attachmentType":"pdf","work_url":"https://www.academia.edu/91084652/Real_Time_3D_Hand_Gesture_Detection_from_Depth_Images","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/91084652/Real_Time_3D_Hand_Gesture_Detection_from_Depth_Images"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="71931898" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/71931898/A_New_Approach_For_Hand_Gestures_Recognition_Based_on_Depth_Map_Captured_by_RGB_D_Camera">A New Approach For Hand Gestures Recognition Based on Depth Map Captured by RGB-D Camera</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="173259952" href="https://independent.academia.edu/WalidMahdi1">Walid Mahdi</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Computación y Sistemas, 2016</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A New Approach For Hand Gestures Recognition Based on Depth Map Captured by RGB-D Camera","attachmentId":81072890,"attachmentType":"pdf","work_url":"https://www.academia.edu/71931898/A_New_Approach_For_Hand_Gestures_Recognition_Based_on_Depth_Map_Captured_by_RGB_D_Camera","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/71931898/A_New_Approach_For_Hand_Gestures_Recognition_Based_on_Depth_Map_Captured_by_RGB_D_Camera"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="90332115" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/90332115/Robust_gesture_recognition_using_Kinect_A_comparison_between_DTW_and_HMM">Robust gesture recognition using Kinect: A comparison between DTW and HMM</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="244426882" href="https://independent.academia.edu/JagdishLalRaheja">Jagdish Lal Raheja</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Optik, 2015</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Robust gesture recognition using Kinect: A comparison between DTW and HMM","attachmentId":93924286,"attachmentType":"pdf","work_url":"https://www.academia.edu/90332115/Robust_gesture_recognition_using_Kinect_A_comparison_between_DTW_and_HMM","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/90332115/Robust_gesture_recognition_using_Kinect_A_comparison_between_DTW_and_HMM"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="78733491" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/78733491/Dynamic_Gesture_Recognition_for_Natural_Human_System_Interaction">Dynamic Gesture Recognition for Natural Human System Interaction</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="31008616" href="https://um5a.academia.edu/FakhitaRegragui">Fakhita Regragui</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2016</p><p class="ds-related-work--abstract ds2-5-body-sm">This paper addresses two problems: 3d dynamic gesture recognition and gesture misallocation. In order to solve these problems, we propose a new approach which combines Hidden Markov Models (HMM) and Dynamic Time Warping (DTW). The proposed approach has two main phases; first, recognizing gestures using a hidden Markov model. Second, avoiding misallocation by rejecting gestures based on a threshold computed using DTW. Our database includes many samples of five gestures obtained with a Kinect and described by depth information only. The results show that our approach yields good gesture classification without any misallocation and it is robust against environmental constraints.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Dynamic Gesture Recognition for Natural Human System Interaction","attachmentId":85676431,"attachmentType":"pdf","work_url":"https://www.academia.edu/78733491/Dynamic_Gesture_Recognition_for_Natural_Human_System_Interaction","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/78733491/Dynamic_Gesture_Recognition_for_Natural_Human_System_Interaction"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":109098734,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":109098734,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_109098734" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. You can download the paper by clicking the button above.</p></div></div></div></div><div class="ds-sidebar--container js-work-sidebar"><div class="ds-related-content--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="0" data-entity-id="83643142" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/83643142/Using_Depth_Cameras_for_Recognition_and_Segmentation_of_Hand_Gestures">Using Depth Cameras for Recognition and Segmentation of Hand Gestures</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="14663020" href="https://independent.academia.edu/jalawiSulaiman">jalawi Alshudukhi</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Advances in Materials Science and Engineering, 2021</p><div 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