학술논문

A novel and robust algorithm to model handwriting skill for haptic applications
Document Type
Conference
Source
2009 IEEE International Conference on Systems, Man and Cybernetics Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on. :2912-2917 Oct, 2009
Subject
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Power, Energy and Industry Applications
Robustness
Haptic interfaces
Writing
Hidden Markov models
Humans
USA Councils
Spline
Handwriting recognition
Cybernetics
Aerospace engineering
Multiresolution modeling
haptics
virtual reality training
handwriting
calligraphy
human motor skill
Language
ISSN
1062-922X
Abstract
A necessary step to building effective writing skill training system requires developing good methods for modeling human skill adequately. A number of groups have represented character information in various languages for writing skill based on trajectory information. These methods are often data intensive, tedious to implement and do not encode force information. To overcome these restrictions a novel present a novel modeling methodology that has good accuracy, robustness, flexibility and encodes force information involved in writing characters. This modeling methodology, based on Global-Local Approximation technique, has the capability to provide temporal force or position information independent of time, decoupling velocity information of the sample data used to capture skilled tasks. This modeling approach can be extended many human skilled tasks such as surgery, art and sports