An Approach to Glove-Based Gesture Recognition

Parvini, Farid; McLeod, Dennis; Shahabi, Cyrus; Navai, Bahareh; Zali, Baharak; Ghandeharizadeh, Shahram

doi:10.1007/978-3-642-02577-8_26

Cited by 21 publications

(11 citation statements)

References 7 publications

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“…Many previous studies on hand gesture recognition have been conducted using gloves fitted with sensors, such as the works of [13][14][15][16][17][18][19]. However, despite some remarkable successes, this method remains challenging owing to its complexity as well as variable glove sizes between users.…”

Section: Sensors Used For Hand Gesture Recognition Interfacementioning

confidence: 99%

Real-Time Hand Gesture Spotting and Recognition Using RGB-D Camera and 3D Convolutional Neural Network

Tran

Yang

et al. 2020

Applied Sciences

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Using hand gestures is a natural method of interaction between humans and computers. We use gestures to express meaning and thoughts in our everyday conversations. Gesture-based interfaces are used in many applications in a variety of fields, such as smartphones, televisions (TVs), video gaming, and so on. With advancements in technology, hand gesture recognition is becoming an increasingly promising and attractive technique in human–computer interaction. In this paper, we propose a novel method for fingertip detection and hand gesture recognition in real-time using an RGB-D camera and a 3D convolution neural network (3DCNN). This system can accurately and robustly extract fingertip locations and recognize gestures in real-time. We demonstrate the accurateness and robustness of the interface by evaluating hand gesture recognition across a variety of gestures. In addition, we develop a tool to manipulate computer programs to show the possibility of using hand gesture recognition. The experimental results showed that our system has a high level of accuracy of hand gesture recognition. This is thus considered to be a good approach to a gesture-based interface for human–computer interaction by hand in the future.

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Section: Sensors Used For Hand Gesture Recognition Interfacementioning

confidence: 99%

Real-Time Hand Gesture Spotting and Recognition Using RGB-D Camera and 3D Convolutional Neural Network

Tran

Yang

et al. 2020

Applied Sciences

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“…From these works, it has been identified the following specified shortcomings [3,4,5,6,7,8,9,10,11,12,13,14,15]:…”

Section: Related Workmentioning

confidence: 99%

Gestural Interaction for Virtual Reality Environments through Data Gloves

Rodríguez¹,

Jofré²,

Alvarado³

et al. 2017

Adv. sci. technol. eng. syst. j.

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“…Hand gesture recognition techniques can be divided mainly in to two categories (Parvini et al, 2009) which are;…”

Section: Gesture Recognitionmentioning

confidence: 99%

Review on sign language recognition methods for supporting communication between deaf and non-deaf persons

Silva

Fernando

2011

IJCVR

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With the rapid development of information and communication technology (ICT), the communication sector has improved continuously. Artificial intelligence (AI) is a field which has a broad, highly technical and specialised research area focusing on different types of sub areas and has generated a lot of interest with many novel applications in the IT world. Along with recent developments in image processing, AI has also been used to automatically recognise sign language gestures, in what is known as automatic sign language recognition (ASLR).This paper reviews methods of facilitating the communication between deaf and non-deaf persons.

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An Approach to Glove-Based Gesture Recognition

Cited by 21 publications

References 7 publications

Real-Time Hand Gesture Spotting and Recognition Using RGB-D Camera and 3D Convolutional Neural Network

Real-Time Hand Gesture Spotting and Recognition Using RGB-D Camera and 3D Convolutional Neural Network

Gestural Interaction for Virtual Reality Environments through Data Gloves

Review on sign language recognition methods for supporting communication between deaf and non-deaf persons

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