Results 11 to 20 of about 143,707 (286)
IEEE Access, 2022 To solve the problem of the low recognition rate of continuous dynamic gestures in Chinese sign language, a non-invasive end-to-end continuous dynamic gesture recognition system combining Inertial Measurement Unit (IMU) signal and surface ...
Jinquan Li +3 more
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RECOGNITION OF DYNAMIC LITHUANIAN LANGUAGE GESTURES
Mokslas - Lietuvos ateitis, 2023 This paper proposes a method for automated Lithuanian hands gestures data collection and for Lithuanian hands gestures classification. The dataset of 1100 samples was collected for 10 different classes of Lithuanian hands gesture. The features of hands gestures were extracted with CNN network. The classification was made with LSTM network.
Arnas Karmonas, Andrius Katkevičius
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Robust Hand Gesture Recognition Based on RGB-D Data for Natural Human–Computer Interaction
IEEE Access, 2022 To naturally interact with virtual environment by hand gesture, this paper presents a robust RGB-D data based recognition method of static and dynamic hand gesture.
Jun Xu +3 more
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Data glove-based gesture recognition using CNN-BiLSTM model with attention mechanism.
PLoS ONE, 2023 As a novel form of human machine interaction (HMI), hand gesture recognition (HGR) has garnered extensive attention and research. The majority of HGR studies are based on visual systems, inevitably encountering challenges such as depth and occlusion.
Jiawei Wu +5 more
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Micro-motion Hand Gesture Recognition Method Based on Improved Multiple Dimensional Convolution Neural Network [PDF]
Jisuanji gongcheng, 2018 For the traditional Two Dimensional Convolutional Neural Network(2D-CNN),the time dimension information is lost,and thus the dynamic gesture cannot be recognized.This paper proposes a novel dynamic hand gesture recognition method based on video streams ...
LI Lingxia,WANG Yu,WU Jinjun,WANG Shasha
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, 2021 The Human-Machine Interaction (HMI) research field is an important topic in machine learning that has been deeply investigated thanks to the rise of computing power in the last years. The first time, it is possible to use machine learning to classify images and/or videos instead of the traditional computer vision algorithms. The aim of this paper is to
Bokstaller, Jonas +1 more
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Deep Learning Based Real-Time Recognition of Dynamic Finger Gestures Using a Data Glove
IEEE Access, 2020 In this article, a real-time dynamic finger gesture recognition using a soft sensor embedded data glove is presented, which measures the metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joint angles of five fingers. In the gesture recognition
Minhyuk Lee, Joonbum Bae
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Hidden‐Markov‐Models‐Based Dynamic Hand Gesture Recognition [PDF]
Mathematical Problems in Engineering, 2012 This paper is concerned with the recognition of dynamic hand gestures. A method based on Hidden Markov Models (HMMs) is presented for dynamic gesture trajectory modeling and recognition. Adaboost algorithm is used to detect the user′s hand and a contour‐based hand tracker is formed combining condensation and partitioned sampling.
Xiaoyan Wang +4 more
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Dynamic Gesture Recognition System with Gesture Spotting Based on Self-Organizing Maps
Applied Sciences, 2021 In this paper, a real-time dynamic hand gesture recognition system with gesture spotting function is proposed. In the proposed system, input video frames are converted to feature vectors, and they are used to form a posture sequence vector that ...
Hiroomi Hikawa +3 more
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Real time hand gesture recognition including hand segmentation and tracking [PDF]
, 2006 In this paper we present a system that performs automatic gesture recognition. The system consists of two main components: (i) A unified technique for segmentation and tracking of face and hands using a skin detection algorithm along with handling ...
A. Shamaie +4 more
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