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Proceedings ArticleDOI

Low-Cost Gesture Detector Using Neural Networks

TLDR
This project proposes a novel low cost approach to gesture recognition using neural networks for end user applications control in contrary to more expensive devices prevalent in the market.
Abstract
This project proposes a novel low cost approach to gesture recognition using neural networks for end user applications control in contrary to more expensive devices prevalent in the market. The final outcome is proposed to be a versatile product with variety of applications which can cater to many user needs. In fact, a person with minimal programming knowledge can design an application with the proposed and prototyped device. The use of neural networks has made this possible, as the pattern recognition of neural networks is highly accurate than conventional programming.

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References
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Journal ArticleDOI

A survey of glove-based input

TL;DR: A detailed overview of the field of glove-based input devices can be found in this paper, where the authors provide a basis for understanding the field by describing key hand-tracking technologies and applications using gloves.
Journal ArticleDOI

Hand gesture recognition using a real-time tracking method and hidden Markov models

TL;DR: A hand gesture recognition system to recognize continuous gesture before stationary background consisting of a real time hand tracking and extraction, feature extraction, hidden Markov model (HMM) training, and gesture recognition.
Proceedings ArticleDOI

A real-time continuous gesture recognition system for sign language

TL;DR: A large vocabulary sign language interpreter is presented with real-time continuous gesture recognition of sign language using a data glove using hidden Markov models for 51 fundamental postures, 6 orientations, and 8 motion primitives.
Journal ArticleDOI

MEMS Accelerometer Based Nonspecific-User Hand Gesture Recognition

TL;DR: A recognition algorithm based on sign sequence and template matching as presented in this paper can be used for nonspecific-users hand-gesture recognition without the time consuming user-training process prior to gesture recognition.
Journal ArticleDOI

Real-time gesture recognition system and application

TL;DR: A vision-based system that can interpret a user's gestures in real time to manipulate windows and objects within a graphical user interface and users who tested it found the gestures intuitive and the application easy to use.
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