Search results for "Gesture Recognition"

showing 10 items of 25 documents

Body Gestures and Spoken Sentences: A Novel Approach for Revealing User’s Emotions

2017

In the last decade, there has been a growing interest in emotion analysis research, which has been applied in several areas of computer science. Many authors have con- tributed to the development of emotion recognition algorithms, considering textual or non verbal data as input, such as facial expressions, gestures or, in the case of multi-modal emotion recognition, a combination of them. In this paper, we describe a method to detect emotions from gestures using the skeletal data obtained from Kinect-like devices as input, as well as a textual description of their meaning. The experimental results show that the correlation existing between body movements and spoken user sentence(s) can be u…

0209 industrial biotechnologyComputer scienceSpeech recognitionGesture Recognition02 engineering and technologycomputer.software_genreEmotion Recognition Gesture Recognition Sentiment AnalysisNonverbal communication020901 industrial engineering & automationSentiment Analysis0202 electrical engineering electronic engineering information engineeringEmotion recognitionSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniFacial expressionSettore INF/01 - Informaticabusiness.industry020207 software engineeringGesture recognitionEmotion RecognitionArtificial intelligencebusinesscomputerSentenceNatural language processingMeaning (linguistics)Gesture2017 IEEE 11th International Conference on Semantic Computing (ICSC)
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Implicit visual analysis in handedness recognition.

1998

In the present study, we addressed the problem of whether hand representations, derived from the control of hand gesture, are used in handedness recognition. Pictures of hands and fingers, assuming either common or uncommon postures, were presented to right-handed subjects, who were required to judge their handedness. In agreement with previous results (Parsons, 1987, 1994; Gentilucci, Daprati, & Gangitano, 1998), subjects recognized handedness through mental movement of their own hand in order to match the posture of the presented hand. This was proved by a control experiment of physical matching. The new finding was that presentation of common finger postures affected responses differ…

AdultMaleVisual perceptionhandedness gesture recognitionrecognition (psychology)media_common.quotation_subjectExperimental and Cognitive PsychologySettore BIO/09Functional LateralityCognitionArts and Humanities (miscellaneous)PerceptionDevelopmental and Educational PsychologyHumansmedia_commonGesturesBody movementCognitionRecognition PsychologyHandVisual PerceptionFemaleMale; gestures; recognition (psychology); female; hand; functional laterality; adult; visual perception; cognition; humansPsychologyIntuitionMental imageCognitive psychologyGestureConsciousness and cognition
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Pose classification using support vector machines

2000

In this work a software architecture is presented for the automatic recognition of human arm poses. Our research has been carried on in the robotics framework. A mobile robot that has to find its path to the goal in a partially structured environment can be trained by a human operator to follow particular routes in order to perform its task quickly. The system is able to recognize and classify some different poses of the operator's arms as direction commands like "turn-left", "turn-right", "go-straight", and so on. A binary image of the operator silhouette is obtained from the gray-level input. Next, a slice centered on the silhouette itself is processed in order to compute the eigenvalues …

Artificial neural networkCovariance matrixbusiness.industryComputer scienceBinary imagePattern recognitionMobile robotSilhouetteSupport vector machineOperator (computer programming)Gesture recognitionComputer visionArtificial intelligencebusinessEigenvalues and eigenvectorsProceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium
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Robust Hand Gestures Recognition Using a Deep CNN and Thermal Images

2021

Medical systems and assistive technologies, human-computer interaction, human-robot interaction, industrial automation, virtual environment control, sign language translation, crisis and disaster management, entertainment and computer games, and so on all use RGB cameras for hand gesture recognition. However, their performance is limited especially in low-light conditions. In this paper, we propose a robust hand gesture recognition system based on high-resolution thermal imaging that is light-independent. A dataset of 14,400 thermal hand gestures is constructed, separated into two color tones. We also propose using a deep CNN to classify high-resolution hand gestures accurately. The propose…

Computer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONSign languagecomputer.software_genreAutomationVirtual machineGesture recognitionBenchmark (computing)RGB color modelComputer visionArtificial intelligenceElectrical and Electronic EngineeringbusinessInstrumentationcomputerEdge computingGestureIEEE Sensors Journal
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Gesture Modeling by Hanklet-Based Hidden Markov Model

2015

In this paper we propose a novel approach for gesture modeling. We aim at decomposing a gesture into sub-trajectories that are the output of a sequence of atomic linear time invariant (LTI) systems, and we use a Hidden Markov Model to model the transitions from the LTI system to another. For this purpose, we represent the human body motion in a temporal window as a set of body joint trajectories that we assume are the output of an LTI system. We describe the set of trajectories in a temporal window by the corresponding Hankel matrix (Hanklet), which embeds the observability matrix of the LTI system that produced it. We train a set of HMMs (one for each gesture class) with a discriminative a…

Conditional random fieldKinectbusiness.industryComputer scienceMaximum-entropy Markov modelAction ClassificationHankel matrixMarkov modelHidden Markov ModelLTI system theoryGestureAction RecognitionGesture recognitionObservabilityArtificial intelligencebusinessHidden Markov modelAlgorithmHankel matrixSkeleton
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A gesture recognition framework for exploring museum exhibitions

2018

In this paper we present a gesture recognition framework for providing the visitors of a museum exhibition with a non intrusive interface for the multimedia enjoyment of digital contents. Early experiments were carried out at the Computer History Museum Exhibition of the University of Palermo.

ExhibitionComputer historySettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniAmbient intelligence Gesture recognition Human computer interactionGesture recognitionComputer scienceInterface (computing)0202 electrical engineering electronic engineering information engineering020206 networking & telecommunications020201 artificial intelligence & image processing02 engineering and technologyVisual arts
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A System for Simultaneous People Tracking and Posture Recognition in the context of Human-Computer Interaction

2005

The paper deals with an artificial-vision based system for simultaneous people tracking and posture recognition In the context of human-computer Interaction. We adopt no particular assumptions on the movement of a person and on Its appearance, making the system suitable to several real-world applications. The system can be roughly subdivided Into two highly correlated phases: tracking and recognition. The tracking phase Is concerned with establishing coherent relations of the same subject between frames. We adopted the Condensation algorithm due to Its robustness In highly cluttered environments. The recognition phase adopts a modified elgenspace technique In order to classify between sever…

ExploitComputer sciencebusiness.industryPosture recognitionTrackingHuman Posture recognitionRoboticsFacial recognition systemMachine visionRobustness (computer science)Gesture recognitionPattern recognitionActivity recognitionEye trackingComputer visionHuman computer interactionCondensation algorithmArtificial intelligenceVisual trackingbusinessGesture
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Gesture recognition using low-cost devices: Techniques, applications, perspectives

2016

Negli ultimi anni abbiamo assistito ad una grande diffusione dei cosiddetti “Kinect-like devices”, ovvero dispositivi basati su un insieme di sensori a basso costo, che consentono di ottenere un’immagine di profondità della scena ripresa. L’alta accessibilità di questi dispositivi, principalmente in termini di costi, ne ha facilitato la diffusione nell’ambito del riconoscimento dei gesti in numerose applicazioni, sia commerciali che di ricerca. In questo articolo saranno inizialmente illustrati i principi generali su cui si fondano le principali tecniche utilizzate per riconoscere i gesti, sfruttando i dati ottenibili dai dispositivi “Kinect-like”. Successivamente, saranno presentati alcuni…

Gesture recognitionSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniTouchless interactionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMedia TechnologyKinect-like devicesComputer Science Applications1707 Computer Vision and Pattern RecognitionInformation SystemInformation Systems; Computer Science Applications1707 Computer Vision and Pattern Recognition; Media TechnologyHuman-computer interactionInformation Systems
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Fully automatic, real-time detection of facial gestures from generic video

2005

A technique for the detection of facial gestures from low resolution video sequences is presented. The technique builds upon the automatic 3D head tracker formulation of [M. La Cascia et al., 2000]. The tracker is based on the registration of a texture-mapped cylindrical model. Facial gesture analysis is performed in the texture map by assuming that the residual registration error can be modeled as a linear combination of facial motion templates. Two formulations are proposed and tested. In one formulation, the head and facial motion are estimated in a single, combined linear system. In the other formulation, head motion and then facial motion are estimated in a two-step process. The two-st…

Head (linguistics)Computer sciencebusiness.industryLinear systemComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registrationMotion (physics)Image textureGesture recognitionComputer visionArtificial intelligencebusinessTexture mappingComputingMethodologies_COMPUTERGRAPHICSGestureIEEE 6th Workshop on Multimedia Signal Processing, 2004.
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Fundamentals of automated human gesture recognition using 3D integral imaging: a tutorial

2020

Automated human gesture recognition is receiving significant research interest, with applications ranging from novel acquisition techniques to algorithms, data processing, and classification methodologies. This tutorial presents an overview of the fundamental components and basics of the current 3D optical image acquisition technologies for gesture recognition, including the most promising algorithms. Experimental results illustrate some examples of 3D integral imaging, which are compared to conventional 2D optical imaging. Examples of classifying human gestures under normal and degraded conditions, such as low illumination and the presence of partial occlusions, are provided. This tutorial…

Integral imagingData processingbusiness.industryComputer scienceImage qualityComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONautomated human gesture recognitionRangingImage processing02 engineering and technology021001 nanoscience & nanotechnology01 natural sciencesAtomic and Molecular Physics and Optics010309 opticsoptical imagingStatistical classification3D integral imagingGesture recognition0103 physical sciencesComputer visionArtificial intelligence0210 nano-technologybusinessGestureAdvances in Optics and Photonics
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