The State of the Art in Online Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Specifying gestures by example
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Myth of the Paperless Office
The Myth of the Paperless Office
A Pen-Based Interface for Real-Time Document Edition
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
iGesture: A General Gesture Recognition Framework
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
Paperproof: a paper-digital proof-editing system
CHI '08 Extended Abstracts on Human Factors in Computing Systems
Improving handwriting recognition by the use of semantic information
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
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In this paper we present a system which recognizes handwritten annotations on printed text documents and interprets their semantic meaning. This system processes in three steps. In the first step, document analysis methods are applied to identify possible gestures and text regions. In the second step, the text and gestures are recognized using several state-of-the-art recognition methods. In the fourth step, the actual marked text is identified. Finally, the recognized information is sent to the Semantic Desktop, the personal Semantic Web on the Desktop computer, which supports users in their information management. In order to assess the performance of the system, we have performed an experimental study. We evaluated the different stages of the system and measured the overall performance.