Hand Tracking and Gesture Recognition for Human-Computer Interaction

Manresa, Cristina; Varona, Javier; Mas, Ramon; Perales, F.

doi:10.5565/rev/elcvia.109

Cited by 150 publications

(61 citation statements)

References 12 publications

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“…Machine Learning based on Hidden Markov Models (HMMs). Cristina Manresa, Javier Varona, Ramon Mas and Francisco J. Perales [1], presents a techniques based on the probability that a new pixel of skin can be calculated. To prevent errors from hand segmentation the second step is hand tracking.…”

Section: Related Workmentioning

confidence: 99%

Boltay Hath for Indian Sign Language Recognition

kaur¹,

Banga²

2014

IJAIS

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In this research work it is discussed that how a gesture recognition system for alphabetical hand gestures is built. The main motive was to develop a system that can simplify the way that the normal human being interact with the deaf and dump people without the need of interpretator . This system also provides the easy way of humans interaction with computers. This system is designed using MATLAB instead of neural network. In this system Eigen vector and Eigen value techniques only in MATLAB are used. The basis of our method is a fast detection process to obtain the meaningful hand region from the whole image, which is able to deal with a large number of hand gestures against different indoor backgrounds and lighting condition, and a recognition process that identifies the hand gestures from the images of the normalized hand. Experiments show that the system can achieve a 99% recognition rate and is suitable for real-time applications.

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Section: Related Workmentioning

confidence: 99%

Boltay Hath for Indian Sign Language Recognition

kaur¹,

Banga²

2014

IJAIS

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“…Tan and Wu described hand state by image moments [11]. Boreki and Zimmer employed contour and its curvature analysis [12], while Manresa et al used contour and convex hull [13]. Both methods allow for extracting information on the actual hand shape (e.g.…”

Section: ____________________________________________________________mentioning

confidence: 99%

Sixth Sense Technology Based Pointer Interface System

Jadhav¹

2015

IJRITCC

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Abstract:As computers became more common in society, promoting natural human to computer interaction (HCI) will have a positive influence on their use. Hence, there has been growing interest in the development of new approaches and technologies for bridging the human-computer barrier. A Real Time Vision Based Pointer interface system is a new vision-based interface, which is sufficiently fast and effective to substitute a computer mouse. System is able to reduce hardware impact and also increases range of usage of physical word objects instead of digital word objects like mouse. The aim of a system is to bring HCI to a level where interactions with computers will be as natural as an interaction between humans.

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“…The system can work in real time on a conventional processor. We propose a color-based segmentation method based on the segmentation approach in [6]. Particle Filter algorithm [7] is employed to locate hand position accurately and efficiently.…”

Section: Introductionmentioning

confidence: 99%

Vision-based Hand Gesture Interaction Using Particle Filter, Principle Component Analysis and Transition Network

Wang¹,

Zhang²,

Wang³

et al. 2014

J. Inf. Comput. Sci.

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Vision-based human-computer interaction is becoming important nowadays. It offers natural interaction with computers and frees users from mechanical interaction devices, which is favourable especially for wearable computers. This paper presents a human-computer interaction system based on a conventional webcam and hand gesture recognition. This interaction system works in real time and enables users to control a computer cursor with hand motions and gestures instead of a mouse. Five hand gestures are designed on behalf of five mouse operations: moving, left click, left-double click, right click and no-action. An algorithm based on Particle Filter is used for tracking the hand position. PCA-based feature selection is used for recognizing the hand gestures. A transition network is also employed for improving the accuracy and reliability of the interaction system. This interaction system shows good performance in the recognition and interaction test.

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Hand Tracking and Gesture Recognition for Human-Computer Interaction

Cited by 150 publications

References 12 publications

Boltay Hath for Indian Sign Language Recognition

Boltay Hath for Indian Sign Language Recognition

Sixth Sense Technology Based Pointer Interface System

Vision-based Hand Gesture Interaction Using Particle Filter, Principle Component Analysis and Transition Network

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