Creating Note Taking Solutions Software Design Engineer/Test Lead Challenges in

Tablet PC Opportunity Mobile PC’s showing faster growth than desktops Faster rate of innovation than desktops Tablet ecosystem maturing Great development platform Opportunity for innovation

Preview: Next Generation lnk Analysis Single API that couples Layout Analysis with Handwriting Recognition Available in Longhorn timeframe Available in Managed and C++/COM layers Available in Managed and C++/COM layers Provides developer with a robust API to enable advanced note taking scenarios for end users

lnk Analysis: Overview Improved Writing/Drawing classification Advanced classification engines: Annotations, shape detection Supports user-corrected structures and results Seamless support for multilanguage content Improved support for digital form filling Analysis results stored in a tree structure

Four Challenges Ink reflow User correction Robust annotation support Rich diagram support

Challenge One: Ink Reflow Text is not bound to visual attributes : Ink has visual attributes Text stream has no visual or location properties Ink has visual attributes Strokes have a location relative to the document and other strokes Strokes contain color, thickness, opacity, etc. as part of the data Requires knowledge about context of Ink strokes

Ink Analysis: Ink Reflow Deterministic objects provided to the application from analysis results Paragraphs, Lines, Words, and Drawings Logical objects are paired with ink data Improved selection model Application can react to document sizing changes based on layout analysis Basic reflow support reveals other advanced scenarios Annotations, Diagrams, Flowcharts

Challenge Two: User Correction Users write differently! Correction of recognition results Choose from alternative results Enabling user-specified results Correction of Layout Results Correction of Layout Results Change Writing/Drawing classification Change grouping Solutions may have subtle but important impact Enhanced conversion of ink to text Searching handwritten notes for keywords Ability for the user to persist changes is critical Must be easy, intuitive, and fast

Ink Analysis: User Correction Accurate results reduce the need to correct Provides a mechanism to persist user changes Enables applications to expose a variety of ways that user can correct analysis results Recognition strings, along with segmentation alternates Layout results: Writing/Drawing, Grouping Layout results: Writing/Drawing, Grouping Annotation types and anchor points Annotation types and anchor points Analysis ‘hints’ allow biasing of results

Challenge Three: Robust Annotation Support Two annotation classes: Ink on Text Ink on Ink Interpreting types of annotations Containers, callouts, connectors, and more Containers, callouts, connectors, and more Determining annotation anchor points for reflow scenarios Requires context of Ink strokes and location of annotated text

Ink Analysis: Robust Annotation Support Annotation engine supports a variety of annotation types Context of annotations is known Relationships between multiple annotation objects is provided Anchor points provided to application

Challenge Four: Rich Diagram Support Requires shape recognition Determining relationships between shapes as well as shapes to writing is critical Requires ability to perform shape, container and connector detection

Ink Analysis: Rich Diagram Support Writing/Drawing classification supports common shapes Coupled with the annotation support, application becomes aware of drawing context: DiagramsFlowcharts

Summary The Tablet PC form factor enables great scenarios that were not previously available on a desktop or laptop. The opportunity for innovation spans many more areas than covered here. InkAnalysis is a preview – look for it in the Longhorn timeframe.

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