Search results for: gesture recognition - Bridge of Knowledge

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Search results for: gesture recognition

Search results for: gesture recognition

  • A cortex-like model for animal recognition based on texture using feature-selective hashing

    Publication

    - Year 2014

  • Gesture recognition framework for multimedia content viewer controlling

    Publication

    In 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...

  • Pose classification in the gesture recognition using the linear optical sensor

    Publication

    Gesture 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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  • Lip movement and gesture recognition for a multimodal human-computer interface

    Publication

    - Year 2009

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  • Hand gesture recognition supported by fuzzy rules and Kalman filters

    The 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....

  • Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks

    In 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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  • LECTURE NOTES IN COMPUTER SCIENCE

    Journals

    ISSN: 0302-9743

  • Examining Feature Vector for Phoneme Recognition

    Publication

    - Year 2018

    The aim of this paper is to analyze usability of descriptors coming from music information retrieval to the phoneme analysis. The case study presented consists in several steps. First, a short overview of parameters utilized in speech analysis is given. Then, a set of time and frequency domain-based parameters is selected and discussed in the context of stop consonant acoustical characteristics. A toolbox created for this purpose...

  • Face Recognition: Shape versus Texture

    Publication

    - Year 2015

    This paper describes experiments related to the application of well-known techniques of the texture feature extraction (Local Binary Patterns and Gabor filtering) to the problem of automatic face verification. Results of the tests show that simple image normalization strategy based on the eye center detection and a regular grid of fiducial points outperforms the more complicated approach, employing active models that are able to...

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  • Human-Computer Interface Based on Visual Lip Movement and Gesture Recognition

    The multimodal human-computer interface (HCI) called LipMouse is presented, allowing a user to work on a computer using movements and gestures made with his/her mouth only. Algorithms for lip movement tracking and lip gesture recognition are presented in details. User face images are captured with a standard webcam. Face detection is based on a cascade of boosted classifiers using Haar-like features. A mouth region is located in...

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  • Investigating Feature Spaces for Isolated Word Recognition

    Publication

    - Year 2018

    Much attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...

  • Feature extraction in detection and recognition of graphical objects

    Publication

    - Year 2022

    Detection and recognition of graphic objects in images are of great and growing importance in many areas, such as medical and industrial diagnostics, control systems in automation and robotics, or various types of security systems, including biometric security systems related to the recognition of the face or iris of the eye. In addition, there are all systems that facilitate the personal life of the blind people, visually impaired...

  • Investigating Feature Spaces for Isolated Word Recognition

    Publication
    • P. Treigys
    • G. Korvel
    • G. Tamulevicius
    • J. Bernataviciene
    • B. Kostek

    - Year 2020

    The study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...

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  • Fuzzy rule-based dynamic gesture recognition employing camera & multimedia projector

    Publication

    - Year 2010

    In 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

    Journals

    ISSN: 1568-1475 , eISSN: 1569-9773

  • Examining Classifiers Applied to Static Hand Gesture Recognition in Novel Sound Mixing System

    The 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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  • Auditory-model based robust feature selection for speech recognition

    Publication

    - Journal of the Acoustical Society of America - Year 2010

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  • Local Texture Pattern Selection for Efficient Face Recognition and Tracking

    This paper describes the research aimed at finding the optimal configuration of the face recognition algorithm based on local texture descriptors (binary and ternary patterns). Since the identification module was supposed to be a part of the face tracking system developed for interactive wearable computer, proper feature selection, allowing for real-time operation, became particularly important. Our experiments showed that it is...

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  • Video recordings of static hand gestures for gesture based interaction

    Open Research Data
    open access

    This 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...

  • Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition

    Publication

    - JOURNAL OF THE AUDIO ENGINEERING SOCIETY - Year 2018

    convolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...

  • A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces

    Publication
    • G. Tamulevicius
    • G. Korvel
    • A. B. Yayak
    • P. Treigys
    • J. Bernataviciene
    • B. Kostek

    - Electronics - Year 2020

    In this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on the acoustic representation...

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  • Examining Feature Vector for Phoneme Recognition / Analiza parametrów w kontekście automatycznej klasyfikacji fonemów

    Publication

    - Year 2017

    The aim of this paper is to analyze usability of descriptors coming from music information retrieval to the phoneme analysis. The case study presented consists in several steps. First, a short overview of parameters utilized in speech analysis is given. Then, a set of time and frequency domain-based parameters is selected and discussed in the context of stop consonant acoustical characteristics. A toolbox created for this purpose...

  • Surface EMG-based signal acquisition for decoding hand movements

    Open Research Data
    open access

    Biosignal 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...

  • Emotion Recognition

    Open Research Data
    open access - series: Person A

    The films presented here were recorded using so-called high-speed camera Phantom Miro. To play the movie  You need the special software which can be downloaded from the web site https://www.phantomhighspeed.com/resourcesandsupport/phantomresources/pccsoftware the details of the movie are available after starting the movie in the viewer in the description...

  • Emotion Recognition

    Open Research Data
    open access - series: Person A

    The films presented here were recorded using so-called high-speed camera Phantom Miro. To play the movie  You need the special software which can be downloaded from the web site https://www.phantomhighspeed.com/resourcesandsupport/phantomresources/pccsoftware the details of the movie are available after starting the movie in the viewer in the description...

  • Gesture-based computer control system

    In 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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  • Edyta Gołąb-Andrzejak dr hab.

  • Uncertainty in emotion recognition

    Purpose–The purpose of this paper is to explore uncertainty inherent in emotion recognition technologiesand the consequences resulting from that phenomenon.Design/methodology/approach–The paper is a general overview of the concept; however, it is basedon a meta-analysis of multiple experimental and observational studies performed over the past couple of years.Findings–The mainfinding of the paper might be summarized as follows:...

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  • Recognition and sensing of anions

    Publication

    Molecular ion recognition is one of the most intensively studied areas of supramolecular technology. The reason for this is the essential role that ions play in many biological as well as industrial processes. On the other hand, however, it has been proved that ions can have a negative impact on human health and the environment. For these reasons, it is extremly important to develop rapid and simple methods allowing the determination...

  • Testing A Novel Gesture-Based Mixing Interface

    With 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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  • Analysis of Properties of an Active Linear Gesture Sensor

    Basic 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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  • Bożena Kostek prof. dr hab. inż.

  • COGNITION

    Journals

    ISSN: 0010-0277 , eISSN: 1873-7838

  • Improved Procedures for Feature-Based Suppression of Surface Texture High-Frequency Measurement Errors in the Wear Analysis of Cylinder Liner Topographies

    Publication

    - Metals - Year 2021

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  • GAIT & POSTURE

    Journals

    ISSN: 0966-6362 , eISSN: 1879-2219

  • Venture Capital

    Journals

    ISSN: 1369-1066 , eISSN: 1464-5343

  • Gesture-controlled Sound Mixing System With a Sonified Interface

    Publication

    - Year 2013

    In 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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  • The passive operating mode of the linear optical gesture sensor

    The study evaluates the influence of natural light conditions on the effectiveness of the linear optical gesture sensor, working in the presence of ambient light only (passive mode). The orientations of the device in reference to the light source were modified in order to verify the sensitivity of the sensor. A criterion for the differentiation between two states - "possible gesture" and "no gesture" - was proposed. Additionally,...

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  • Semi complex navigation with an active optical gesture sensor

    This paper presents the methods of diversified touchless interactions between a user and a mobile platform utilizing the optical gesture sensor. The sensor uses 8 photodiodes to measure the reflected light in the active mode (using embedded LEDs) or it measures shadows caused by fingers in the passive mode. Several algorithms were implemented: automatic mode switching, adaptive illumination level compensation, resolution improvements...

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  • Human emotion recognition with biosignals

    Publication

    - Year 2022

    This chapter presents issues in the field of affective computing. Basic preliminary information for the recognition of emotions is given and models of emotions, various ways of evoking emotions, as well as their theoretical foundations are discussed. The particular attention is given to the use of physiological signals in recognizing emotions. This subject is outlined further below by presenting selected biosignals, their relationship...

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  • Language Models in Speech Recognition

    Publication

    - Year 2022

    This chapter describes language models used in speech recognition, It starts by indicating the role and the place of language models in speech recognition. Mesures used to compare language models follow. An overview of n-gram, syntactic, semantic, and neural models is given. It is accompanied by a list of popular software.

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  • Emotion Recognition and Its Applications

    The paper proposes a set of research scenarios to be applied in four domains: software engineering, website customization, education and gaming. The goal of applying the scenarios is to assess the possibility of using emotion recognition methods in these areas. It also points out the problems of defining sets of emotions to be recognized in different applications, representing the defined emotional states, gathering the data and...

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  • Recognition of environmentally important ions

    Publication

    - Logistyka - Year 2013

    ..

  • Recognition of Hand Drawn Flowcharts

    Publication

    - Year 2013

    In this paper the problem of hand drawn flowcharts recognition is presented. There are described two attitudes to this problem: on-line and off-line. A concept of FCE, a system for recognizing and understanding of freehand drawn on-line flow charts on desktop computer and mobile devices is presented. The first experiments with the FCE system and the planes for future are also described.

  • Integration in Multichannel Emotion Recognition

    Publication

    - Year 2018

    The paper concerns integration of results provided by automatic emotion recognition algorithms. It presents both the challenges and the approaches to solve them. Paper shows experimental results of integration. The paper might be of interest to researchers and practitioners who deal with automatic emotion recognition and use more than one solution or multichannel observation.

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  • Gesture-based computer control system applied to the interactive whiteboard

    In 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...

  • Gesture-based computer control system applied to the interactive whiteboard

    Publication

    - Year 2010

    In 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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  • Viruses, cancer and non-self recognition

    Publication
    • M. Padariya
    • U. Kalathiya
    • S. Mikac
    • K. Dziubek
    • M. Tovar
    • E. Sroka
    • R. Fahraeus
    • A. Sznarkowska

    - Open Biology - Year 2021

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  • Guido: a musical score recognition system

    Publication

    - Year 2007

    This paper presents an optical music recognition system Guido that can automatically recognize the main musical symbols of music scores that were scanned or taken by a digital camera. The application is based on object model of musical notation and uses linguistic approach for symbol interpretation and error correction. The system offers musical editor with a partially automatic error correction.

  • System for automatic singing voice recognition

    W artykule przedstawiono system automatycznego rozpoznawania jakości i typu głosu śpiewaczego. Przedstawiono bazę danych oraz zaimplementowane parametry. Algorytmem decyzyjnym jest algorytm sztucznych sieci neuronowych. Wytrenowany system decyzyjny osiąga skuteczność ok. 90% w obydwu kategoriach rozpoznawania. Dodatkowo wykazano przy pomocy metod statystycznych, że wyniki działania systemu automatycznej oceny jakości technicznej...