Consumer electronics control system based on hand gesture moment invariants

نویسندگان

  • Prashan Premaratne
  • Q. Nguyen
چکیده

Almost all consumer electronic equipment today uses remote controls for user interfaces. However, the variety of physical shapes and functional commands that each remote control features also raises numerous problems: the difficulties in locating the required remote control, the confusion with the button layout, the replacement issue and so on. The consumer electronics control system using hand gestures is a new innovative user interface that resolves the complications of using numerous remote controls for domestic appliances. Based on one unified set of hand gestures, this system interprets the user hand gestures into pre-defined commands to control one or many devices simultaneously. The system has been tested and verified under both incandescent and fluorescent lighting conditions. The experimental results are very encouraging as the system produces real-time responses and highly accurate recognition towards various gestures. Disciplines Physical Sciences and Mathematics Publication Details This article was originally published as Premaratne, P, and Nguyen, Q, Consumer electronics control system based on hand gesture moment invariants, IET Computer Vision, 1(1), 2007, 35-41. Copyright 2007 IET. This journal article is available at Research Online: http://ro.uow.edu.au/infopapers/605 Consumer electronics control system based on hand gesture moment invariants P. Premaratne and Q. Nguyen Abstract: Almost all consumer electronic equipment today uses remote controls for user interfaces. However, the variety of physical shapes and functional commands that each remote control features also raises numerous problems: the difficulties in locating the required remote control, the confusion with the button layout, the replacement issue and so on. The consumer electronics control system using hand gestures is a new innovative user interface that resolves the complications of using numerous remote controls for domestic appliances. Based on one unified set of hand gestures, this system interprets the user hand gestures into pre-defined commands to control one or many devices simultaneously. The system has been tested and verified under both incandescent and fluorescent lighting conditions. The experimental results are very encouraging as the system produces real-time responses and highly accurate recognition towards various gestures. Almost all consumer electronic equipment today uses remote controls for user interfaces. However, the variety of physical shapes and functional commands that each remote control features also raises numerous problems: the difficulties in locating the required remote control, the confusion with the button layout, the replacement issue and so on. The consumer electronics control system using hand gestures is a new innovative user interface that resolves the complications of using numerous remote controls for domestic appliances. Based on one unified set of hand gestures, this system interprets the user hand gestures into pre-defined commands to control one or many devices simultaneously. The system has been tested and verified under both incandescent and fluorescent lighting conditions. The experimental results are very encouraging as the system produces real-time responses and highly accurate recognition towards various gestures.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Hand gesture tracking and recognition system using Lucas-Kanade algorithms for control of consumer electronics

Dynamic hand gesture tracking and recognition system can simplify the way humans interact with computers and many other non-critical consumer electronic equipments. This system is based on the well-known ‘‘Wave Controller’’ technology developed at the University of Wollongong [1–3] and certainly a step forward in video gaming and consumer electronics control interfaces. Currently, computer inte...

متن کامل

Neural Network Performance Analysis for Real Time Hand Gesture Tracking Based on Hu Moment and Hybrid Features

This paper presents a comparison study between the multilayer perceptron (MLP) and radial basis function (RBF) neural networks with supervised learning and back propagation algorithm to track hand gestures. Both networks have two output classes which are hand and face. Skin is detected by a regional based algorithm in the image, and then networks are applied on video sequences frame by frame in...

متن کامل

A Real-Time Hand Gesture Interface Implemented on a Multi-Core Processor

This paper describes a real-time hand gesture recognition system and its application to VCR remote control. Cascaded classifiers are used to detect a number of different hand poses. In order to detect a hand in real time, the detection algorithm is optimized for multi-core processors by distributing the operations to multiple cores and minimizing the data transmission between them. We have impl...

متن کامل

Comparison of 2D and 3D Analysis For Automated Cued Speech Gesture Recognition

This paper deals with the problem of the automated classification of cued speech gestures. Cued speech is a specific gesture language (different from the sign language) used for communication between deaf people and other people. It uses only 8 different hand configurations. The aim of this work is to apply a simple classifier on 3 images data sets, in order to answer two main questions: is 3D ...

متن کامل

A Comparative Study on Using Zernike Velocity Moments and Hidden Markov Models for Hand Gesture Recognition

Hand-gesture recognition presents a challenging problem for computer vision due to the articulated structure of the human hand and the complexity of the environments in which it is typically applied. Solving such a problem requires a robust tracking mechanism which in turn depends on an effective feature descriptor and classifier. Moment invariants, as discriminative feature descriptors, have b...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017