Real-time and Embedded Detection of Hand Gestures with an IMU-based Glove PDF Download
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Author: Chaithanya Kumar Mummadi
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Chaithanya Kumar Mummadi
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Xiaoliang Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages : 69
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Internet of wearable things (IoWT) has been used to exchange the information with other devices in recent years, regarding to provide body health information and make the wearables as a biomarker, many researchers such as scientists in the academia or engineers in the industry are trying to design a more reliable and smarter system in the fields of IoWT. This thesis described a novel upper limbs (hand and arm) motion detection system which used cooperative wearable sensing network consists of wearable armband and smart glove made by customizable pressure sensor arrays to detect personal dynamic hand gestures. The strength of such "cooperative wearable sensing network" is to reduce false positive with multi-sensors information fusion. A deep learning technique "Long Short-Term Memory" algorithm had been computed to build an effective model to classify hand gestures by training and testing the collected IMU (Inertial Measurement Unit), Electromyography (EMG), finger and palm's pressure data. In the experiments, this IoWT system was evaluated in common hand gesture recognition and specific scenario in smart health: smoking cessation study. Wearable sensors have the potential to improve current approaches by providing personalized feedback and objective verification of smoking status. This thesis combined the proposed IoWT system in hand gesture recognition with an Android software application to monitor smoking in real-time by detecting smoking and non-smoking dynamic hand gestures in daily life, such as "answering the phone", "drinking", "writing", etc. Findings have implications for using cooperative sensing technology in HGR fields and tobacco cessation treatment delivery and assessment of smoking status. This thesis describes wearable sensor systems design, Android things framework to establish a cooperative wearable sensing network, and streaming sensor data analysis through deep learning. A controlled smoking cessation pilot study was used as a case study to evaluate the design consideration and system performance of the developed IoWT system.
Author: Kane, Lalit
Publisher: IGI Global
ISBN: 1799894363
Category : Computers
Languages : en
Pages : 249
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Due to the rise of new applications in electronic appliances and pervasive devices, automated hand gesture recognition (HGR) has become an area of increasing interest. HGR developments have come a long way from the traditional sign language recognition (SLR) systems to depth and wearable sensor-based electronic devices. Where the former are more laboratory-oriented frameworks, the latter are comparatively realistic and practical systems. Based on various gestural traits, such as hand postures, gesture recognition takes different forms. Consequently, different interpretations can be associated with gestures in various application contexts. A considerable amount of research is still needed to introduce more practical gesture recognition systems and associated algorithms. Challenges and Applications for Hand Gesture Recognition highlights the state-of-the-art practices of HGR research and discusses key areas such as challenges, opportunities, and future directions. Covering a range of topics such as wearable sensors and hand kinematics, this critical reference source is ideal for researchers, academicians, scholars, industry professionals, engineers, instructors, and students.
Author: Ankit Chaudhary
Publisher: Springer
ISBN: 9811047987
Category : Technology & Engineering
Languages : en
Pages : 108
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This book focuses on light invariant bare hand gesture recognition while there is no restriction on the types of gestures. Observations and results have confirmed that this research work can be used to remotely control a robotic hand using hand gestures. The system developed here is also able to recognize hand gestures in different lighting conditions. The pre-processing is performed by developing an image-cropping algorithm that ensures only the area of interest is included in the segmented image. The segmented image is compared with a predefined gesture set which must be installed in the recognition system. These images are stored and feature vectors are extracted from them. These feature vectors are subsequently presented using an orientation histogram, which provides a view of the edges in the form of frequency. Thereby, if the same gesture is shown twice in different lighting intensities, both repetitions will map to the same gesture in the stored data. The mapping of the segmented image's orientation histogram is firstly done using the Euclidian distance method. Secondly, the supervised neural network is trained for the same, producing better recognition results. An approach to controlling electro-mechanical robotic hands using dynamic hand gestures is also presented using a robot simulator. Such robotic hands have applications in commercial, military or emergency operations where human life cannot be risked. For such applications, an artificial robotic hand is required to perform real-time operations. This robotic hand should be able to move its fingers in the same manner as a human hand. For this purpose, hand geometry parameters are obtained using a webcam and also using KINECT. The parameter detection is direction invariant in both methods. Once the hand parameters are obtained, the fingers’ angle information is obtained by performing a geometrical analysis. An artificial neural network is also implemented to calculate the angles. These two methods can be used with only one hand, either right or left. A separate method that is applicable to both hands simultaneously is also developed and fingers angles are calculated. The contents of this book will be useful for researchers and professional engineers working on robotic arm/hand systems.
Author: Madhusudan Singh
Publisher: Springer Nature
ISBN: 3030684490
Category : Computers
Languages : en
Pages : 526
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The two-volume set LNCS 12615 + 12616 constitutes the refereed proceedings of the 12th International Conference on Intelligent Human Computer Interaction, IHCI 2020, which took place in Daegu, South Korea, during November 24-26, 2020. The 75 full and 18 short papers included in these proceedings were carefully reviewed and selected from a total of 185 submissions. The papers were organized in topical sections named: cognitive modeling and system; biomedical signal processing and complex problem solving; natural language, speech, voice and study; algorithm and related applications; crowd sourcing and information analysis; intelligent usability and test system; assistive living; image processing and deep learning; and human-centered AI applications.
Author: Masaaki Kurosu
Publisher: Springer Nature
ISBN: 3031355962
Category : Computers
Languages : en
Pages : 631
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The four-volume set LNCS 14011, 14012, 14013, and 14014 constitutes the refereed proceedings of the Human Computer Interaction thematic area of the 25th International Conference on Human-Computer Interaction, HCII 2023, which took place in Copenhagen, Denmark, in July 2023. A total of 1578 papers and 396 posters have been accepted for publication in the HCII 2023 proceedings from a total of 7472 submissions. The papers included in the HCI 2023 volume set were organized in topical sections as follows: Part I: Design and evaluation methods, techniques and tools; interaction methods and techniques; Part II: Children computer interaction; emotions in HCI; and understanding the user experience; Part III: Human robot interaction; chatbots and voice-based interaction; interacting in the metaverse; Part IV: Supporting health, quality of life and everyday activities; HCI for learning, culture, creativity and societal impact.
Author: Harkeerat Kaur
Publisher: Springer Nature
ISBN: 3031581814
Category :
Languages : en
Pages : 635
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Author: Xuesong Qiu
Publisher: Springer Nature
ISBN: 9819971616
Category : Technology & Engineering
Languages : en
Pages : 362
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This conference proceedings is a collection of the accepted papers of ISCC2023 - the 7th International Conference on Information Science, Communication and Computing held in Chongqing, China, 2-5 June 2023. The topics focus on intelligent information science and technology, artificial intelligence and intelligent systems, cloud computing and big data, smart computing and communication technology, wireless network, and cyber security. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows, and undergraduate and graduate students who need to build a knowledge base of the latest advances and state of the practice in the topics covered by this conference proceedings. This will enable them to build, maintain and manage systems of high reliability and complexity. We would like to thank the authors for their hard work and dedication, and the reviewers for ensuring that only the highest quality papers were selected.
Author: Nasser Hasan Abdel-Qader Dardas
Publisher:
ISBN:
Category : Gesture
Languages : en
Pages :
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This thesis focuses on bare hand gesture recognition by proposing a new architecture to solve the problem of real-time vision-based hand detection, tracking, and gesture recognition for interaction with an application via hand gestures. The first stage of our system allows detecting and tracking a bare hand in a cluttered background using face subtraction, skin detection and contour comparison. The second stage allows recognizing hand gestures using bag-of-features and multi-class Support Vector Machine (SVM) algorithms. Finally, a grammar has been developed to generate gesture commands for application control. Our hand gesture recognition system consists of two steps: offline training and online testing. In the training stage, after extracting the keypoints for every training image using the Scale Invariance Feature Transform (SIFT), a vector quantization technique will map keypoints from every training image into a unified dimensional histogram vector (bag-of-words) after K-means clustering. This histogram is treated as an input vector for a multi-class SVM to build the classifier. In the testing stage, for every frame captured from a webcam, the hand is detected using my algorithm. Then, the keypoints are extracted for every small image that contains the detected hand posture and fed into the cluster model to map them into a bag-of-words vector, which is fed into the multi-class SVM classifier to recognize the hand gesture. Another hand gesture recognition system was proposed using Principle Components Analysis (PCA). The most eigenvectors and weights of training images are determined. In the testing stage, the hand posture is detected for every frame using my algorithm. Then, the small image that contains the detected hand is projected onto the most eigenvectors of training images to form its test weights. Finally, the minimum Euclidean distance is determined among the test weights and the training weights of each training image to recognize the hand gesture. Two application of gesture-based interaction with a 3D gaming virtual environment were implemented. The exertion videogame makes use of a stationary bicycle as one of the main inputs for game playing. The user can control and direct left-right movement and shooting actions in the game by a set of hand gesture commands, while in the second game, the user can control and direct a helicopter over the city by a set of hand gesture commands.
Author: João M. F. Rodrigues
Publisher: Springer
ISBN: 3030227502
Category : Computers
Languages : en
Pages : 828
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The five-volume set LNCS 11536, 11537, 11538, 11539, and 11540 constitutes the proceedings of the 19th International Conference on Computational Science, ICCS 2019, held in Faro, Portugal, in June 2019. The total of 65 full papers and 168 workshop papers presented in this book set were carefully reviewed and selected from 573 submissions (228 submissions to the main track and 345 submissions to the workshops). The papers were organized in topical sections named: Part I: ICCS Main Track Part II: ICCS Main Track; Track of Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Track of Agent-Based Simulations, Adaptive Algorithms and Solvers; Track of Applications of Matrix Methods in Artificial Intelligence and Machine Learning; Track of Architecture, Languages, Compilation and Hardware Support for Emerging and Heterogeneous Systems Part III: Track of Biomedical and Bioinformatics Challenges for Computer Science; Track of Classifier Learning from Difficult Data; Track of Computational Finance and Business Intelligence; Track of Computational Optimization, Modelling and Simulation; Track of Computational Science in IoT and Smart Systems Part IV: Track of Data-Driven Computational Sciences; Track of Machine Learning and Data Assimilation for Dynamical Systems; Track of Marine Computing in the Interconnected World for the Benefit of the Society; Track of Multiscale Modelling and Simulation; Track of Simulations of Flow and Transport: Modeling, Algorithms and Computation Part V: Track of Smart Systems: Computer Vision, Sensor Networks and Machine Learning; Track of Solving Problems with Uncertainties; Track of Teaching Computational Science; Poster Track ICCS 2019 Chapter “Comparing Domain-decomposition Methods for the Parallelization of Distributed Land Surface Models” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
