Implicit structure for pen-based systems within a freeform interaction paradigm
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Sketching for knowledge capture: a progress report
Proceedings of the 7th international conference on Intelligent user interfaces
Introduction to Algorithms
Indexing and Retrieval of On-line Handwritten Documents
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Perceptually-supported image editing of text and graphics
Proceedings of the 16th annual ACM symposium on User interface software and technology
Representations, feature extraction, matching and relevance feedback for sketch retrieval
Representations, feature extraction, matching and relevance feedback for sketch retrieval
Hierarchical parsing and recognition of hand-sketched diagrams
Proceedings of the 17th annual ACM symposium on User interface software and technology
Recognition and Grouping of Handwritten Text in Diagrams and Equations
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
A graph-matching approach to dynamic media allocation in intelligent multimedia interfaces
Proceedings of the 10th international conference on Intelligent user interfaces
Multi-domain sketch understanding
Multi-domain sketch understanding
Structuralizing digital ink for efficient selection
Proceedings of the 11th international conference on Intelligent user interfaces
Multimodal error correction for continuous handwriting recognition in pen-based user interfaces
Proceedings of the 11th international conference on Intelligent user interfaces
Crossmodal error correction of continuous handwriting recognition by speech
Proceedings of the 12th international conference on Intelligent user interfaces
InkSeine: In Situ search for active note taking
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes
Proceedings of the 20th annual ACM symposium on User interface software and technology
OZCHI '07 Proceedings of the 19th Australasian conference on Computer-Human Interaction: Entertaining User Interfaces
Sketch retrieval and relevance feedback with biased SVM classification
Pattern Recognition Letters
Structuring and manipulating hand-drawn concept maps
Proceedings of the 14th international conference on Intelligent user interfaces
Retrieval of online handwriting by synthesis and matching
Pattern Recognition
Recognition of hand drawn chemical diagrams
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Combining geometry and domain knowledge to interpret hand-drawn diagrams
Computers and Graphics
Intelligent understanding of handwritten geometry theorem proving
Proceedings of the 15th international conference on Intelligent user interfaces
Digital concept maps for managing knowledge and information
Knowledge and Information Visualization
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Concept maps are an important tool to organize, represent, and share knowledge. Building a concept map involves creating text-based concepts and specifying their relationships with line-based links. Current concept map tools usually impose specific task structures for text and link construction, and may increase cognitive burden to generate and interact with concept maps. While pen-based devices (e.g., tablet PCs) offer users more freedom in drawing concept maps with a pen or stylus more naturally, the support for hand-drawn concept map creation and manipulation is still limited, largely due to the lack of methods to recognize the components and structures of hand-drawn concept maps. This article proposes a method to understand hand-drawn concept maps. Our algorithm can extract node blocks, or concept blocks, and link blocks of a hand-drawn concept map by combining dynamic programming and graph partitioning, recognize the text content of each concept node, and build a concept-map structure by relating concepts and links. We also design an algorithm for concept map retrieval based on hand-drawn queries. With our algorithms, we introduce structure-based intelligent manipulation techniques and ink-based retrieval techniques to support the management and modification of hand-drawn concept maps. Results from our evaluation study show high structure recognition accuracy in real time of our method, and good usability of intelligent manipulation and retrieval techniques.