Adrien Delaye

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We present a new system for predicting the segmentation of online handwritten documents into multiple blocks, such as text paragraphs, tables, graphics, or mathematical expressions. A hierarchical representation of the document is adopted by aggregating strokes into blocks, and interactions between different levels are modeled in a tree Conditional Random(More)
Free-form online handwritten documents contain a high diversity of content, organized without constraints imposed to the user. The lack of prior knowledge about content and layout makes the modeling of contextual information of crucial importance for interpretation of such documents. In this work, we present a comprehensive investigation of the sources of(More)
The hierarchical nature of Chinese characters has inspired radical-based recognition, but radical segmentation from characters remains a challenge. We previously proposed a radical-based approach for online handwritten Chinese character recognition, which incorporates character structure knowledge into integrated radical segmentation and recognition, and(More)
As the rise of pen-enabled interfaces is accompanied with an increased number of techniques for recognition of penbased input, recent trends in symbol recognition show an escalation in systems complexity (number of features, classifiers combination) or the over-specialization of systems to specific datasets or applications. In spite of the importance of(More)
In this paper, we introduce the Intuidoc-Loustic Gestures DataBase (ILGDB), a new publicly available database of realistic pen-based gestures for evaluation of recognition systems in pen-enabled interfaces. ILGDB was collected in a real world context and in an immersive environment. As it contains a large number of unconstrained user-defined gestures, ILGDB(More)
In this paper, we present a new type of Marking menus. Continuous Marking Menus are specifically dedicated to pen-based interfaces, and designed to define a set of cursive, realistic handwritten gestures. In menu mode, they offer a continuous visual feedback and fluent exploration of menu hierarchy, inviting the user to execute cursive gestures for invoking(More)