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Challenges and Applications for Hand Gesture Recognition

Author: Kane, Lalit

Publisher: IGI Global

Published: 2022-03-25

Total Pages: 249

ISBN-13: 1799894363

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.

Face Detection and Gesture Recognition for Human-Computer Interaction

Author: Ming-Hsuan Yang

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 188

ISBN-13: 1461514231

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Traditionally, scientific fields have defined boundaries, and scientists work on research problems within those boundaries. However, from time to time those boundaries get shifted or blurred to evolve new fields. For instance, the original goal of computer vision was to understand a single image of a scene, by identifying objects, their structure, and spatial arrangements. This has been referred to as image understanding. Recently, computer vision has gradually been making the transition away from understanding single images to analyzing image sequences, or video understanding. Video understanding deals with understanding of video sequences, e. g. , recognition of gestures, activities, facial expressions, etc. The main shift in the classic paradigm has been from the recognition of static objects in the scene to motion-based recognition of actions and events. Video understanding has overlapping research problems with other fields, therefore blurring the fixed boundaries. Computer graphics, image processing, and video databases have obvious overlap with computer vision. The main goal of computer graphics is to gener ate and animate realistic looking images, and videos. Researchers in computer graphics are increasingly employing techniques from computer vision to gen erate the synthetic imagery. A good example of this is image-based rendering and modeling techniques, in which geometry, appearance, and lighting is de rived from real images using computer vision techniques. Here the shift is from synthesis to analysis followed by synthesis.

Robust Hand Gesture Recognition for Robotic Hand Control

Author: Ankit Chaudhary

Publisher: Springer

Published: 2017-06-05

Total Pages: 108

ISBN-13: 9811047987

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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.

Gesture Recognition

Author: Qiguang Miao

Publisher: Elsevier

Published: 2024-07-26

Total Pages: 225

ISBN-13: 0443289603

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Gesture Recognition: Theory and Applications covers this important topic in computer science and language technology that has a goal of interpreting human gestures via mathematical algorithms. The book begins by examining the computer vision-based gesture recognition method, focusing on the theory and related research results of various recent gesture recognition technologies. The book takes the evolutions of gesture recognition technology as a clue, systematically introducing gesture recognition methods based on handcrafted features, convolutional neural networks, recurrent neural networks, multimodal data fusion, and visual attention mechanisms. Three gesture recognition-based HCI (Human Computer Interaction) practical cases are introduced. Finally, the book looks at emerging research trends and application. Focuses on the theory and application of gesture recognition, providing a systematic introduction to commonly used datasets in the field as well as algorithms based on handcrafted features, convolutional neural networks, multimodal fusion, and attention mechanisms Introduces the practical applications of gesture recognition in real-world scenarios, enabling readers to enhance their practical application skills while learning about relevant technologies Demonstrates four main categories of gesture recognition methods and analyzes their associated challenges

Gesture Recognition

Author: Sergio Escalera

Publisher: Springer

Published: 2017-07-19

Total Pages: 583

ISBN-13: 3319570218

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This book presents a selection of chapters, written by leading international researchers, related to the automatic analysis of gestures from still images and multi-modal RGB-Depth image sequences. It offers a comprehensive review of vision-based approaches for supervised gesture recognition methods that have been validated by various challenges. Several aspects of gesture recognition are reviewed, including data acquisition from different sources, feature extraction, learning, and recognition of gestures.

Gesture Recognition

Author: Fouad Sabry

Publisher: One Billion Knowledgeable

Published: 2024-05-13

Total Pages: 125

ISBN-13:

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What is Gesture Recognition Gesture recognition is an area of research and development in computer science and language technology concerned with the recognition and interpretation of human gestures. A subdiscipline of computer vision, it employs mathematical algorithms to interpret gestures. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Gesture recognition Chapter 2: Pointing device gesture Chapter 3: User interface Chapter 4: Affective computing Chapter 5: Handheld projector Chapter 6: Tangible user interface Chapter 7: Multimodal interaction Chapter 8: Voice user interface Chapter 9: Wired glove Chapter 10: Multi-touch (II) Answering the public top questions about gesture recognition. (III) Real world examples for the usage of gesture recognition in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Gesture Recognition.

Gesture Recognition

Author: Amit Konar

Publisher: Springer

Published: 2017-07-04

Total Pages: 289

ISBN-13: 3319622129

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This book presents a thorough analysis of gestural data extracted from raw images and/or range data with an aim to recognize the gestures conveyed by the data. It covers image morphological analysis, type-2 fuzzy logic, neural networks and evolutionary computation for classification of gestural data. The application areas include the recognition of primitive postures in ballet/classical Indian dances, detection of pathological disorders from gestural data of elderly people, controlling motion of cars in gesture-driven gaming and gesture-commanded robot control for people with neuro-motor disability. The book is unique in terms of its content, originality and lucid writing style. Primarily intended for graduate students and researchers in the field of electrical/computer engineering, the book will prove equally useful to computer hobbyists and professionals engaged in building firmware for human-computer interfaces. A prerequisite of high school level mathematics is sufficient to understand most of the chapters in the book. A basic background in image processing, although not mandatory, would be an added advantage for certain sections.

Motion Tracking and Gesture Recognition

Author: Carlos Travieso-Gonzalez

Publisher: BoD – Books on Demand

Published: 2017-07-12

Total Pages: 175

ISBN-13: 9535133772

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Nowadays, the technological advances allow developing many applications on different fields. In this book Motion Tracking and Gesture Recognition, two important fields are shown. Motion tracking is observed by a hand-tracking system for surgical training, an approach based on detection of dangerous situation by the prediction of moving objects, an approach based on human motion detection results and preliminary environmental information to build a long-term context model to describe and predict human activities, and a review about multispeaker tracking on different modalities. On the other hand, gesture recognition is shown by a gait recognition approach using Kinect sensor, a study of different methodologies for studying gesture recognition on depth images, and a review about human action recognition and the details about a particular technique based on a sensor of visible range and with depth information.

Gesture Recognition

Author: Gilberto Coleman

Publisher: Nova Science Publishers

Published: 2018

Total Pages: 0

ISBN-13: 9781536134919

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In the opening chapter of Gesture Recognition: Performance, Applications and Features, the authors discuss gesture recognition and its role in the developing world of technology. The possibility of implementing a gesture detection application that works with people with special needs is examined, such as recognition of sign language for the hearing-impaired. Following this, the authors present their approach for face detection and tracking, user identification, facial feature extraction and head pose estimation as the low-level representation of facial gesture atomics. Additionally, an approach for a movement-based facial gestures recognition is presented, with results demonstrated through practical approaches. A later work explores spectral features from algebraic graph theory in static hand gesture recognition. Specifically, we apply a technique that uses the elements of the spectral matrix of the Laplacian to construct symmetric polynomials that are permutation invariants. The values of these polynomials can be used as graph features in a statistical learning pipeline that has the ability of distinguishing between distinct graphs and can reveal graph clusters. In the closing study, the authors developed two algorithms for the detection of pointing gestures and one approach for waving on this technological base and studied their functionality. The goal was to determine whether a combination of both strategies improves and stabilizes detection rates--

Gesture-Based Communication in Human-Computer Interaction

Author: Annelies Braffort

Publisher: Springer Science & Business Media

Published: 2000-01-12

Total Pages: 322

ISBN-13: 3540669353

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This book constitutes the thoroughly refereed post-proceedings of the International Gesture Workshop, GW'99, held in Gif-sur-Yvette, France, in March 1999. The 16 revised long papers and seven revised short papers were carefully reviewed for inclusion in the book. Also included are four invited papers and the transcription of a round table discussion. The papers are organized in sections on human perception and production of gesture, localization and segmentation, recognition, sign language, gesture synthesis and animation, and multimodality.