Sashi Raghupathy

• Microsoft

Shape recognition is performed based on determining whether one or more ink strokes is not part of a shape or a partial shape. Ink strokes are divided into segments and the segments analyzed employing a relative angular distance histogram. The histogram analysis yields stable, incremental, and discriminating featurization results. Neural networks m...

This paper presents a context aware, online immediate-mode diagramming recognition and beautification software for hand-sketched diagrams. The system is independent of stroke-order, -number, -direction and is invariant to scaling, translation and rotation. In our stroke-based recognition model, we propose convexity features along with spatial and t...

We present a user study aimed at helping understand the applicability of pen-computing in desktop environments. The study applied three mouse-and-keyboard-based and three pen-based interaction techniques to six variations of a diagramming task. We ran 18 subjects from a general population and the key finding was that while the mouse and keyboard te...

The analysis, especially the anchoring, of free-form ink annotations on mixed-content digital documents is more difficult than that of documents containing only text. In this paper, first, we present our work on analyzing the common user scenarios of ink annotations and their anchoring in such an environment, and we also present a unified way to de...

This paper proposes a machine learning approach to grouping problems in ink parsing. Starting from an initial segmentation, hypotheses are generated by perturbing local configurations and processed in a high-confidence-first fashion, where the confidence of each hypothesis is produced by a data-driven AdaBoost decision-tree classifier with a set of...

This paper proposes a machine learning approach to grouping problems in ink parsing. Starting from an initial segmentation, hypotheses are generated by perturbing lo- cal configurations and processed in a high-confidence-first fashion, where the confidence of each hypothesis is pro- duced by a data-driven AdaBoost decision-tree classifier with a se...

Complicated by temporal correlations among the strokes and varying distributions of the underlying classes, the drawing/writing classification of ink strokes in a digital ink file poses interesting challenges. In this paper, we present our efforts in addressing some of the issues. First, we describe how we adjust the outputs of the neural network t...

Annotation is an integral part of reading, comprehending, c ommenting, and authoring notes and documents. In this paper we present a system for recognizing annotations in a fle xible digital notebook that may contain a variety of content ranging from text, to images, to handwritten notes.To accomplish the recognition task in real-time makes the com...

Handwritten text lines are prominent structures in freeform digital ink notes and their reliable detection is the foundation to a natural and intelligent interface for note editing and repurposing. This paper presents an optimization method for text line grouping. The global'cost function is designed to find the simplest stroke partitioning to maxi...

This paper presents an integrated approach to parsing textual structure in freeform handwritten notes. Text-graphics classification and text layout analysis are classical problems in printed document analysis, but the irregularity in handwriting and content in freeform notes reveals limitations in existing approaches. We advocate an integrated tech...

Rendering realistic faces and facial expressions requires good mod- els for the reflectance of skin and the motion of the face. We describe a system for modeling, animating, and rendering a face using measured data for geometry, motion, and reflectance, which realistically reproduces the appearance of a par- ticular person's face and facial express...