A video-based text and equation editor for LaTeX
Engineering Applications of Artificial Intelligence
Touch & Write: a multi-touch table with pen-input
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Feature representations for the recognition of 3D emblematic gestures
HBU'10 Proceedings of the First international conference on Human behavior understanding
A new approach to signature-based authentication
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
| Hi-index | 0.00 |
Abstract: The use of handwriting provides a natural way of inter-acting with small portable computers. However, in order to capture handwritten text on-line special input devices are necessary. Therefore, Munich & Perona [13] proposed to use visual input for pen-based computers. Writing can then be performed on ordinary paper and pen trajectories are automatically extracted from image sequences recorded during the writing process. On the basis of this work we developed a complete video-based on-line handwriting recognition system. We will present the techniques applied for pen tracking, pre-processing, feature extraction, and statistical modeling and recognition. Evaluation results on a writer independent unconstrained handwriting recognition task demonstrate that the inherent limitations of the video-based approach can be compensated using robust modeling combined with adaptation techniques.