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Search results for: HAND GESTURES
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Music Mixing Process Controlled by Hand Gestures
PublicationW referacie przedstawiono system umożliwiający sterowanie procesami miksowania śladów nagrania muzycznego za pomocą gestów rąk. Przybliżono podstawy wielomodalnej percepcji argumentujące potrzebę powstania tego typu systemu oraz założenia przyjęte w trakcie jego tworzenia. Część sprzętowa systemu składa się z rzutnika multimedialnego, kamery internetowej, komputera klasy PC z zainstalowanym oprogramowaniem systemu oraz ekranu dla...
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Basic Hand Gestures Classification Based on Surface Electromyography
PublicationThis paper presents an innovative classification system for hand gestures using 2-channel surface electromyography analysis. The system developed uses the Support Vector Machine classifier, for which the kernel function and parameter optimisation are conducted additionally by the Cuckoo Search swarm algorithm. The system developed is compared with standard Support Vector Machine classifiers with various kernel functions. The average...
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Towards Contactless, Hand Gestures-Based Control of Devices
PublicationGesture-based intuitive interactions with electronic devices can be an important part of smart home systems. In this paper, we adapt the contactless linear gesture sensor for the navigation of smart lighting system. Set of handled gestures allow to propose two methods of active light source selection, continuous dimming, and turning on and off based on discrete gestures. The average gesture recognition accuracy was 97.58% in the...
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Video recordings of static hand gestures for gesture based interaction
Open Research DataThis data set contains video recording of selected simple hand gestures related to sign language. The purpose of the data set is to evaluate different computer algorithms design for hand gesture detection as well as for hand features and hand pose detection and identification. The data set contains 5 video recordings in mp4 format. Each recording is...
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Michał Lech dr inż.
PeopleMichał Lech was born in Gdynia in 1983. In 2007 he graduated from the faculty of Electronics, Telecommunications and Informatics of Gdansk University of Technology. In June 2013, he received his Ph.D. degree. The subject of the dissertation was: “A Method and Algorithms for Controlling the Sound Mixing Processes by Hand Gestures Recognized Using Computer Vision”. The main focus of the thesis was the bias of audio perception caused...
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Surface EMG-based signal acquisition for decoding hand movements
Open Research DataBiosignal processing plays a crucial role in modern hand prosthetics. The challenge is to restore functionality of a lost limb based on the signals acquired from the surface of the stump. The number of sensors (emg channels) used for signal acquisition influence the quality of a prosthetic hand. Modern algorithms (including neural networks) can significantly...
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Gesture-based computer control system
PublicationIn the paper a system for controlling computer applications by hand gestures is presented. First, selected methods used for gesture recognition are described. The system hardware and a way of controlling a computer by gestures are described. The architecture of the software along with hand gesture recognition methods and algorithms used are presented. Examples of basic and complex gestures recognized by the system are given.
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Virtual touchpad - video-based multimodal interface
PublicationA new computer interface named Virtual-Touchpad (VTP) is presented. The Virtual-Touchpad provides a multimodal interface which enables controlling computer applications by hand gestures captured with a typical webcam. The video stream is processed in the software layer of the interface. Hitherto existing video-based interfaces analyzing frames of hand gestures are presented. Then, the hardware configuration and software features...
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The American Sign Language alphabet
Open Research DataThe American Sign Language dataset contains all static letters of the American alphabet, meaning those that do not require movement to perform (the entire alphabet except for the letters 'J' and 'Z', which are dynamic and require hand movement).
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Hand gesture recognition supported by fuzzy rules and Kalman filters
PublicationThe paper presents a system based on camera and multimediaprojector enabling a user to control computer applications by dynamic hand gestures. Gesture recognition methodology based on representing hand movement trajectory by motion vectors analysed using fuzzy rule-based inference is first given. For effective hand position tracking Kalman filters are employed. The system engineered is developed using J2SE and C++/OpenCV technology....
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Testing A Novel Gesture-Based Mixing Interface
PublicationWith a digital audio workstation, in contrast to the traditional mouse-keyboard computer interface, hand gestures can be used to mix audio with eyes closed. Mixing with a visual representation of audio parameters during experiments led to broadening the panorama and a more intensive use of shelving equalizers. Listening tests proved that the use of hand gestures produces mixes that are aesthetically as good as those obtained using...
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Examining Classifiers Applied to Static Hand Gesture Recognition in Novel Sound Mixing System
PublicationThe main objective of the chapter is to present the methodology and results of examining various classifiers (Nearest Neighbor-like algorithm with non-nested generalization (NNge), Naive Bayes, C4.5 (J48), Random Tree, Random Forests, Artificial Neural Networks (Multilayer Perceptron), Support Vector Machine (SVM) used for static gesture recognition. A problem of effective gesture recognition is outlined in the context of the system...
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Interactions using passive optical proximity detector
PublicationIn this paper we evaluated the possible application of a passive, optical sensor as an interface for human-smart glasses interactions. The designed proximity sensor is composed of set of photodiodes and the appropriate hardware and software components. First, experiments were performed for the estimations of such parameters as distance to an object, its width and velocity. Achieved results were satisfactory. Therefore, next, a...
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Neural network based algorithm for hand gesture detection in a low-cost microprocessor applications
PublicationIn this paper the simple architecture of neural network for hand gesture classification was presented. The network classifies the previously calculated parameters of EMG signals. The main goal of this project was to develop simple solution that is not computationally complex and can be implemented on microprocessors in low-cost 3D printed prosthetic arms. As the part of conducted research the data set EMG signals corresponding...
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Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks
PublicationIn this paper, the optical linear sensor, a representative of low-resolution sensors, was investigated in the multiclass recognition of near-field hand gestures. The recurrent neural network (RNN) with a gated recurrent unit (GRU) memory cell was utilized as a gestures classifier. A set of 27 gestures was collected from a group of volunteers. The 27 000 sequences obtained were divided into training, validation, and test subsets....
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Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions
PublicationIn this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...
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Virtual Whiteboard: A gesture-controlled pen-free tool emulating school whiteboard
PublicationIn the paper the so-called Virtual Whiteboard is presented which may be an alternative solution for modern electronic whiteboards based on electronic pens and sensors. The presented tool enables the user to write, draw and handle whiteboard contents using his/her hands only. An additional equipment such as infrared diodes, infrared cameras or cyber gloves is not needed. The user's interaction with the Virtual Whiteboard computer...
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Automatic Classification of Polish Sign Language Words
PublicationIn the article we present the approach to automatic recognition of hand gestures using eGlove device. We present the research results of the system for detection and classification of static and dynamic words of Polish language. The results indicate the usage of eGlove allows to gain good recognition quality that additionally can be improved using additional data sources such as RGB cameras.
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Gesture recognition framework for multimedia content viewer controlling
PublicationIn the paper a system for controlling a multimedia content viewer by hand gestures is presented. First, selected methods used for gesture recognition are described. Two different application cases of the system, i.e. for multimedia presentation purposes and for multimedia content viewing are outlined. Moreover, a proposal of improvement of the system combining these approaches is also given. The system work cycle is reviewed. The...
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Gesture-based computer control system applied to the interactive whiteboard
PublicationIn the paper the gesture-based computer control system coupled with the dedicated touchless interactive whiteboard is presented. The system engineered enables a user to control any top-most computer application by using one or both hands gestures. First, a review of gesture recognition applications with a focus on methods and algorithms applied is given. Hardware and software solution of the system consisting of a PC, camera, multimedia...
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Gesture-based computer control system applied to the interactive whiteboard
PublicationIn the paper the gesture-based computer control system coupled with the dedicated touchless interactive whiteboard is presented. The system engineered enables a user to control any top-most computer application by using one or both hands gestures. First, a review of gesture recognition applications with a focus on methods and algorithms applied is given. Hardware and software solution of the system consisting of a PC, camera, multimedia...
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Analysis of Properties of an Active Linear Gesture Sensor
PublicationBasic gesture sensors can play a significant role as input units in mobile smart devices. However, they have to handle a wide variety of gestures while preserving the advantages of basic sensors. In this paper a user-determined approach to the design of a sparse optical gesture sensor is proposed. The statistical research on a study group of individuals includes the measurement of user-related parameters like the speed of a performed...
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Pose classification in the gesture recognition using the linear optical sensor
PublicationGesture sensors for mobile devices, which have a capability of distinguishing hand poses, require efficient and accurate classifiers in order to recognize gestures based on the sequences of primitives. Two methods of poses recognition for the optical linear sensor were proposed and validated. The Gaussian distribution fitting and Artificial Neural Network based methods represent two kinds of classification approaches. Three types...
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Fuzzy rule-based dynamic gesture recognition employing camera & multimedia projector
PublicationIn the paper the system based on camera and multimedia projector enabling a user to control computer applications by dynamic hand gestures is presented. The main objective is to present the gesture recognition methodology which bases on representing hand movement trajectory by motion vectors analyzed using fuzzy rule-based inference. The approach was engineered in the system developed with J2SE and C++ / OpenCV technology. OpenCV...
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Gesture-controlled Sound Mixing System With a Sonified Interface
PublicationIn this paper the Authors present a novel approach to sound mixing. It is materialized in a system that enables to mix sound with hand gestures recognized in a video stream. The system has been developed in such a way that mixing operations can be performed both with or without visual support. To check the hypothesis that the mixing process needs only an auditory display, the influence of audio information visualization on sound...
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Metoda i algorytmy sterowania procesami miksowania dźwięku za pomocą gestów w oparciu o analizę obrazu wizyjnego
PublicationGłównym celem rozprawy było opracowanie systemu miksowania dźwięku za pomocą gestów rąk wykonywanych w powietrzu oraz zbadanie możliwości oferowanych przez takie rozwiązanie w porównaniu ze współczesną metodą miksowania sygnałów fonicznych, wykorzystującą środowisko komputera. Opracowany system rozpoznaje zarówno dynamiczne jak i statyczne gesty rąk. Rozpoznawanie gestów dynamicznych zrealizowano w oparciu o metody logiki rozmytej...
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Septic safe interactions with smart glasses in health care
PublicationIn this paper, septic safe methods of interaction with smart glasses, due to the health care environment applications consideration, are presented. The main focus is on capabilities of an optical, proximity-based gesture sensor and eye-tracker input systems. The design of both interfaces is being adapted to the open smart glasses platform that is being developed under the eGlasses project. Preliminary results obtained from the...
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Komputerowo wspomagana klasyfikacja wybranych sygnałów elektromiografii powierzchniowej
PublicationWykorzystywanie sygnałów elektromiografii powierzchniowej (ang. Surface Electromyography, SEMG) w procesach sterowania systemami rehabilitacyjnymi stanowi obecnie standardową procedurę. Popularność SEMG wynika z nieinwazyjności metody oraz możliwości szybkiej i precyzyjnej identyfikacji funkcji mięśniowej. W przypadku osób małoletnich proces klasyfikacji sygnałów jest utrudniony ze względu na mniejsze rozmiary i wyższą dynamikę...
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Sign Language Recognition Using Convolution Neural Networks
PublicationThe objective of this work was to provide an app that can automatically recognize hand gestures from the American Sign Language (ASL) on mobile devices. The app employs a model based on Convolutional Neural Network (CNN) for gesture classification. Various CNN architectures and optimization strategies suitable for devices with limited resources were examined. InceptionV3 and VGG-19 models exhibited negligibly higher accuracy than...