Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual Input for Pen-Based Computers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Fingertip Tracking and Gesture Recognition
IEEE Computer Graphics and Applications
Non-parametric Model for Background Subtraction
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Effective Gaussian Mixture Learning for Video Background Subtraction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multimodal human-computer interaction: A survey
Computer Vision and Image Understanding
A Fingertip Extraction Method and Its Application to Handwritten Alphanumeric Characters Recognition
SITIS '08 Proceedings of the 2008 IEEE International Conference on Signal Image Technology and Internet Based Systems
Non-parametric statistical background modeling for efficient foreground region detection
Machine Vision and Applications
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Robust radial basis function neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Hanzi Lamp: an intelligent guide interface for Chinese character learning
Proceedings of the adjunct publication of the 26th annual ACM symposium on User interface software and technology
Mixture models with skin and shadow probabilities for fingertip input applications
Journal of Visual Communication and Image Representation
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This paper proposes a vision-based fingertip handwriting recognition system to provide an alternative to input devices. Traditional handwriting recognition systems are limited because they require a specific or expensive input device, such as pen, tablet, or touch panel. Recently, cameras have gradually become standard components in many computer-based products. Therefore, a fingertip and camera combination provides a flexible and convenient input device. The proposed system combines fingertip detection, trajectory feature extraction, and character recognition. First, fingertip moving trajectories are tracked and recoded. The proposed cyclic chain code histograms are then obtained from the trajectories and used as features in the following recognition process. An improved radial basis function (RBF) neural network is used to recognize handwritten characters. Experimental results show that the proposed novel input system is feasible and effective. This study also presents possible applications for camera input devices.