Download or read book Human Computer Interaction HCI Intelligent Multimodal Interaction Environments written by Julie A. Jacko and published by Springer. This book was released on 2007-08-24 with total page 1049 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here is the third of a four-volume set that constitutes the refereed proceedings of the 12th International Conference on Human-Computer Interaction, HCII 2007, held in Beijing, China, in July 2007, jointly with eight other thematically similar conferences. It covers multimodality and conversational dialogue; adaptive, intelligent and emotional user interfaces; gesture and eye gaze recognition; and interactive TV and media.

Download or read book Dynamic Hand Gesture Recognition written by Quentin De Smedt and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hand gestures are the most natural and intuitive non-verbal communication medium while using a computer, and related research efforts have recently boosted interest. The area of hand gesture analysis covers hand pose estimation and gesture recognition. Hand pose estimation is considered to be more challenging than other human part estimation due to the small size of the hand, its greater complexity and its important self occlusions. Beside, the development of a precise hand gesture recognition system is also challenging due to high dissimilarities between gestures derived from ad-hoc, cultural and/or individual factors of users. First, we propose an original framework to represent hand gestures by using hand shape and motion descriptors computed on 3D hand skeletal features. Additionally, we create the Dynamic Hand Gesture dataset containing 14 gesture types. Evaluation results show the promising way of using hand skeletal data to perform hand gesture recognition. Then, we extend the study of hand gesture analysis to online recognition. Using a deep learning approach, we employ a transfer learning strategy to learn hand posture and shape features from depth image dataset originally created for hand pose estimation. Second, we model the temporal variations of the hand poses and its shapes using a recurrent deep learning technology. Finally, both information are merged to perform accurate prior detection and recognition of hand gestures. Experiments on two datasets demonstrate that the proposed approach is capable to detect an occurring gesture and to recognize its type far before its end.

Download or read book Robust Hand Gesture Recognition for Robotic Hand Control written by Ankit Chaudhary and published by Springer. This book was released on 2017-06-05 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Challenges and Applications for Hand Gesture Recognition written by Kane, Lalit and published by IGI Global. This book was released on 2022-03-25 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Dynamic Hand Gesture Recognition Using Neural Networks written by Alexandru Matei and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Robust Dynamic Hand Gesture Recognition System with Sparse Steric Haar like Feature written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Continuous Dynamic Hand Gesture Recognition Based on Recurrent Neural Networks Over Skeleton Information written by and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Novel Cost Measures for Robust Recognition of Dynamic Hand Gestures written by Ameya Kulkarni and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision aided automatic hand gesture recognition system plays a vital role in real world human computer interaction applications such as sign language recognition, game controls, virtual reality, intelligent home appliances and assistive robotics. In such systems, when input with a video sequence, the challenging task is to locate the gesturing hand (spatial segmentation) and determine when the gesture starts and ends (temporal segmentation). In this thesis, we use a framework which at its principal has a dynamic space time warping (DSTW) algorithm to simultaneously localize gesturing hand, to find an optimal alignment in time domain between query-model sequences and to compute a matching cost (a measure of how well the query sequence matches with the model sequence) for the query-model pair. Within the context of DSTW, the thesis proposes few novel cost measures to improve the performance of the framework for robust recognition of hand gesture with the help of translation and scale invariant feature vectors extracted at each frame of the input video. The performance of the system is evaluated in a real world scene with cluttered background and in presence of multiple moving skin colored distractors in the background.

Download or read book 2018 10th International Conference on Wireless Communications and Signal Processing WCSP written by IEEE Staff and published by . This book was released on 2018-10-18 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The conference aims to gather international researchers from academia and industry to meet and exchange ideas and recent research works across the broad field of wireless technologies The scope of the conference covers a variety of theoretical and applied topics in the areas of communication theory, wireless communications, wireless networking, and signal processing

Download or read book Real time Dynamic Hand Gesture Recognition System Based on 3D Depth Sensing and Fingertip Features written by 陳郁元 and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book AI based Dynamic Hand Gesture Recognition for MR Glasses written by and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book An Experimental Analysis of Feature Selection for Dynamic Hand Gesture Recognition with Leap Motion Controller written by Chi Fai Lam and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Machine Learning and Big Data Analytics Proceedings of International Conference on Machine Learning and Big Data Analytics ICMLBDA 2021 written by Rajiv Misra and published by Springer Nature. This book was released on 2021-09-29 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for researchers and practitioners in the disciplines of computer science, electronics and telecommunication, information science, and electrical engineering. Machine learning and Big data analytics represent a key ingredients in the industrial applications for new products and services. Big data analytics applies machine learning for predictions by examining large and varied data sets—i.e., big data—to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more informed business decisions.

Download or read book Economical and User Friendly Design of Vision Based Natural User Interface Via Dynamic Hand Gestures written by Richa Golash and published by . This book was released on 2020 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: A vision-based hand gesture recognition technology can bring a revolutionary and beneficial change in the field of human-machine interaction for elderly and special people living at home. Nevertheless, continuous detection and localization of the moving hand region in true-color images are strenuous tasks because the hand is a non-rigid object and occupies a small area in the whole frame. True-color images are also sensitive to light variation, camera-view, and background conditions. To ease the process of hand detection and tracking, researchers prefer advanced cameras equipped with costly sensors. This increases the overall cost of interfaces and also requires technical knowledge to operate them. The second issue in dynamic hand gesture recognition is the unpredictability of hand pose used by the user and the random behavior of the hand movement while performing the hand gesture. Therefore, the use of dynamic hand gestures in vision-based human-machine interaction is limited. The goal of this paper is to propose an economical, and user-friendly, technique for vision-based human-machine interaction via dynamic hand gestures that is user-friendly and affordable by all. The proposed technique can be integrated with any day-to-day machines, for example, washing machines, radio, fans, automated doors, etc.

Download or read book Depth From Defocus A Real Aperture Imaging Approach written by Subhasis Chaudhuri and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Depth recovery is important in machine vision applications when a 3-dimensional structure must be derived from 2-dimensional images. This is an active area of research with applications ranging from industrial robotics to military imaging. This book provides the comprehensive details of the methodology, along with the complete mathematics and algorithms involved. Many new models, both deterministic and statistical, are introduced.

Download or read book Advanced Computing written by Natarajan Meghanathan and published by Springer. This book was released on 2010-12-25 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the third of three parts of the refereed proceedings of the First International Conference on Computer Science and Information Technology, CCSIT 2010, held in Bangalore, India, in January 2011. The 46 revised full papers presented in this volume were carefully reviewed and selected. The papers are organized in topical sections on soft computing, such as AI, Neural Networks, Fuzzy Systems, etc.; distributed and parallel systems and algorithms; security and information assurance; ad hoc and ubiquitous computing; wireless ad hoc networks and sensor networks.

Download or read book Simultaneous Localization and Recognition of Dynamic Hand Gestures written by and published by . This book was released on 2005 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: A method for the simultaneous localization and recognition of dynamic hand gestures is proposed. At the core of this method is a dynamic space-time warping (DSTW) algorithm, that aligns a pair of query and model gestures in both space and time. For every frame of the query sequence, feature detectors generate multiple hand region candidates. Dynamic programming is then used to compute both a global matching cost, which is used to recognize the query gesture, and warping path, which aligns the query and model sequences in time, and also finds the best hand candidate region in every query frame. The proposed framework includes translation invariant recognition of gestures, a desirable property for many HCI systems. The performance of the approach is evaluated on a dataset of hand signed digits gestured by people wearing short sleeve shirts, in front of a background containing other non-hand skin-colored objects. The algorithm simultaneously localizes the gesturing hand and recognizes the hand-signed digit. Although DSTW is illustrated in a gesture recognition setting, the proposed algorithm is a general method for matching time series, that allows for multiple candidate feature vectors to be extracted at each time step.