Download or read book Fast and Reliable Hand Action Recognition written by Jingxin Ou and published by . This book was released on 2014 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this work, we develop a hand action recognition method using a SVM (Support Vector Machine) classifier with HOG (Histogram of Oriented Gradients) features and Motion Vectors. Hand gesture recognition system analyzes the HOG feature using SVM. Hand action recognition system applies motion estimation to the input video, analyze the motion vectors, and then recognize the action using a SVM classifier. Our gesture recognition results show that this method is relatively insensitive to variations in illumination, camera perspective, and background variations. We tested our method on 10000 real life images, which captured on camera under different backgrounds and lighting conditions. We achieved a recognition rate of 94%. In the second part of this thesis, we focus on hand action recognition from videos. Background subtraction is used to obtain the foreground of moving objects. Conceptually, this recognition method is based on motion estimation, searches the block in the current frame, and finds the best match of it in the previous frame. Our hand action recognition results show that 74% of the actions can be successfully recognized.

Download or read book Robust and Reliable Hand Gesture Recognition for Myoelectric Control written by Yuzhou Lin 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 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 Human Action Recognition with Depth Cameras written by Jiang Wang and published by Springer Science & Business Media. This book was released on 2014-01-25 with total page 65 pages. Available in PDF, EPUB and Kindle. Book excerpt: Action recognition technology has many real-world applications in human-computer interaction, surveillance, video retrieval, retirement home monitoring, and robotics. The commoditization of depth sensors has also opened up further applications that were not feasible before. This text focuses on feature representation and machine learning algorithms for action recognition from depth sensors. After presenting a comprehensive overview of the state of the art, the authors then provide in-depth descriptions of their recently developed feature representations and machine learning techniques, including lower-level depth and skeleton features, higher-level representations to model the temporal structure and human-object interactions, and feature selection techniques for occlusion handling. This work enables the reader to quickly familiarize themselves with the latest research, and to gain a deeper understanding of recently developed techniques. It will be of great use for both researchers and practitioners.

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 Advances in Computation and Intelligence written by Zhihua Cai and published by Springer Science & Business Media. This book was released on 2010-10-06 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volumes CCIS 107 and LNCS 6382 constitute the proceedings of the 5th International Symposium, ISICA 2010, held in Wuhan, China, in October 2010. ISICA 2010 attracted 267 submissions and through rigorous reviews 53 papers were included in LNCS 6382. The papers are presented in sections on ANT colony and particle swarm optimization, differential evolution, distributed computing, genetic algorithms, multi-agent systems, multi-objective and dynamic optimization, robot intelligence, statistic learning and system design.

Download or read book Hand Gesture Recognition Using Artificial Neural Networks written by Mohd Amrallah Mustafa and published by . This book was released on 2007 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hand gesture has been part of human communication, where, young children usually communicate by using gesture before they can talk. Adults may have also gesture if they need to or they are indeed mute or deaf. Thus the idea of teaching a machine to also learn gesture is very appealing due to its unique mode of communications. A reliable hand gesture recognition system will make the remote control become obsolete. However, ,any of the a new techniques proposed are complicated to be implemented in real time, especially as a human machine interface. This thesis focuses on recognizing hand gesture in static posture. Since static hand postures not only can express some concepts, but also can act as special transition states in temporal gestures recognition, thus estimating static hand postures is in fact a big topics in gesture recognition. A database consists of 200 gesture images have been built, where five volunteers had help in the making of the database. The images were captured in a controlled enviroment and the postures are free from occulation where the background is uncluttered and the hand is assumed to have been localized. A system was then built to recognize the hand gesture. The captured image will be first preprocessed in order to binarize the palm region, where Sobel edge detection technique has been employed, with later followed by morphological operation. A new feature extraction technique has been developed, based on horizontal and vertical states transition count, and the ration of hand area with the respect to whole area of image. These set of features have been proven to have high intra class dissimilarity attributes. In order to have a system that can be easily trained, artificial neural networks has been chosen in the classification stage. A multilayer perceptron with back-propagation algorithm has been developed, thus the system is actually in-built to be used as a human machine interface. The gesture recognition system has been built and tested in Matlab. Where simulations have shown promising results. The performance of recognition rate in this research is 95% which shows a major improvement in comparison to the available methods.

Download or read book Motion Tracking and Gesture Recognition written by Carlos Travieso-Gonzalez and published by BoD – Books on Demand. This book was released on 2017-07-12 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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 Gesture Recognition 48 Success Secrets 48 Most Asked Questions on Gesture Recognition What You Need to Know written by Phyllis Bruce and published by Emereo Publishing. This book was released on 2014-02 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gesture recognition' is a subject in computer discipline and lingo technics with the objective of explaining mortal signals through arithmetical calculations. Gestures may stem as of whatever animal motion either state however normally stem as of the face either hand. Current centers in the area contain chord acknowledgment as of the face and hand gesticulation acknowledgment. There has never been a Gesture recognition Guide like this. It contains 48 answers, much more than you can imagine; comprehensive answers and extensive details and references, with insights that have never before been offered in print. Get the information you need--fast! This all-embracing guide offers a thorough view of key knowledge and detailed insight. This Guide introduces what you want to know about Gesture recognition. A quick look inside of some of the subjects covered: Hidden Markov model, Gesture recognition, Macintosh - Hardware, Finger tracking - Other tracking techniques, Augmented reality - Input devices, Human-computer interaction - Factors of change, Asimo - Abilities, Qualcomm - Acquisitions, Macintosh computer - Hardware, Immersive technology - Interaction, Kinect - Technology, Artificial intelligence systems integration - OpenAIR Protocol, Outline of Apple Inc. - Companies, Affective computing - Body gesture, Samsung Galaxy S II Plus - Software and services, Ben Goertzel - Papers, Wii Remote, Artificial neural network -, Handheld projectors - Hand gesture recognition, PenPoint OS - Awards and innovation, OpenCV - Applications, FingerWorks, Jaron Lanier - Musical performances, Gesture recognition - Algorithms, Google Inc. - Acquisitions and partnerships, Machine learning - Software, Omek Interactive - Company overview, Tablet computer - Modbook, Finger tracking - Tracking without interface, Tablet computer - Features, Artificial intelligence (video games) - Usage, Ultrabook - History, Remote control - Alternatives, and much more...

Download or read book Gesture Recognition written by Qiguang Miao and published by Elsevier. This book was released on 2024-07-26 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Neural Information Processing written by Haiqin Yang and published by Springer. This book was released on 2020-11-19 with total page 844 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set CCIS 1332 and 1333 constitutes thoroughly refereed contributions presented at the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020.* For ICONIP 2020 a total of 378 papers was carefully reviewed and selected for publication out of 618 submissions. The 191 papers included in this volume set were organized in topical sections as follows: data mining; healthcare analytics-improving healthcare outcomes using big data analytics; human activity recognition; image processing and computer vision; natural language processing; recommender systems; the 13th international workshop on artificial intelligence and cybersecurity; computational intelligence; machine learning; neural network models; robotics and control; and time series analysis. * The conference was held virtually due to the COVID-19 pandemic.

Download or read book Human Computer Interaction Using Hand Gestures written by Prashan Premaratne and published by Springer Science & Business Media. This book was released on 2014-03-20 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human computer interaction (HCI) plays a vital role in bridging the 'Digital Divide', bringing people closer to consumer electronics control in the 'lounge'. Keyboards and mouse or remotes do alienate old and new generations alike from control interfaces. Hand Gesture Recognition systems bring hope of connecting people with machines in a natural way. This will lead to consumers being able to use their hands naturally to communicate with any electronic equipment in their 'lounge.' This monograph will include the state of the art hand gesture recognition approaches and how they evolved from their inception. The author would also detail his research in this area for the past 8 years and how the future might turn out to be using HCI. This monograph will serve as a valuable guide for researchers (who would endeavour into) in the world of HCI.

Download or read book Gesture Recognition written by Gilberto Coleman and published by Nova Science Publishers. This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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--

Download or read book Optimisation Algorithms for Hand Posture Estimation written by Shahrzad Saremi and published by Springer Nature. This book was released on 2019-08-26 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the literature on hand posture estimation using generative methods, identifying the current gaps, such as sensitivity to hand shapes, sensitivity to a good initial posture, difficult hand posture recovery in cases of loss in tracking, and lack of addressing multiple objectives to maximize accuracy and minimize computational cost. To fill these gaps, it proposes a new 3D hand model that combines the best features of the current 3D hand models in the literature. It also discusses the development of a hand shape optimization technique. To find the global optimum for the single-objective problem formulated, it improves and applies particle swarm optimization (PSO), one of the most highly regarded optimization algorithms and one that is used successfully in both science and industry. After formulating the problem, multi-objective particle swarm optimization (MOPSO) is employed to estimate the Pareto optimal front as the solution for this bi-objective problem. The book also demonstrates the effectiveness of the improved PSO in hand posture recovery in cases of tracking loss. Lastly, the book examines the formulation of hand posture estimation as a bi-objective problem for the first time. The case studies included feature 50 hand postures extracted from five standard datasets, and were used to benchmark the proposed 3D hand model, hand shape optimization, and hand posture recovery.

Download or read book Computational Intelligence in Multi Feature Visual Pattern Recognition written by Pramod Kumar Pisharady and published by Springer. This book was released on 2014-05-23 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good inter class discrimination. A Bayesian model of visual attention is described which is effective in handling complex background problem in hand posture recognition. The book provides qualitative and quantitative performance comparisons for the algorithms outlined, with other standard methods in machine learning and computer vision. The book is self-contained with several figures, charts, tables and equations helping the reader to understand the material presented without instruction.

Download or read book Automated Face Analysis Emerging Technologies and Research written by Kim, Daijin and published by IGI Global. This book was released on 2009-03-31 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides related theoretical background to understand the overall configuration and challenging problem of automated face analysis systems"--Provided by publisher.