Microsoft Technology Licensing, LLC

Sergey Aleksandrovich Doroshenko

Oz Solomon

Gary Caldwell

Nathan James Fish

Oussama Elachqar

Badal Yadav

Nima Mohajerin

Erich Søren Finkelstein

Gary Lee Caldwell

Technology is described herein for facilitating a user's interaction with a digital ink document. The technology internally represents the ink document using a data structure having a hierarchy of nodes. The nodes describe respective elements in the ink document. The technology leverages the data structure to identify a set of nodes that grows upon the user's repeated selection of a particular part of the ink document. At each stage of the selection, the technology highlights a set of elements in the ink document that correspond to the current set of identified nodes. According to another illustrative aspect, the technology produces the data structure by modifying an original data structure provided by a text analysis engine. The technology performs this task with the objective of accommodating structured interaction by the user with the ink document.

Selecting content in ink documents using a hierarchical data structure

Ink-processing technology is set forth herein for detecting a gesture that a user performs in the course of interacting with an ink document. The technology operates by identifying a grouping of ink strokes created by the user. The technology then determines whether the grouping expresses a gesture based on a combination of spatial information and image information, both of which describe the grouping. That is, the spatial information describes a sequence of positions traversed by the user in drawing the grouping of ink strokes using an ink capture device, while the image information refers to image content in an image produced by rendering the grouping into image form. The technology also provides a technique for identifying the grouping by successively expanding a region of analysis, to ultimately provide a spatial cluster of ink strokes for analysis.

Detecting ink gestures based on spatial and image data processing

Technology is described herein for parsing an ink document having a plurality of ink strokes. The technology performs stroke-level processing on the plurality of ink strokes to produce stroke-level information, the stroke-level information identifying at least one characteristic associated with each ink stroke. The technology also performs object-level processing on individual objects within the ink document to produce object-level information, the object-level information identifying one or more groupings of ink strokes in the ink document. The technology then parses the ink document into constituent parts based on the stroke-level information and the object-level information. In some implementations, the technology converts the ink stroke data into an ink image. The stroke-level processing and/or the object-level processing may operate on the ink image using one or more neural networks. More specifically the stroke-level processing can classify pixels in the input image, while the object-level processing can identify bounding boxes containing possible objects.

Parsing an ink document using object-level and stroke-level processing

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Sergey Aleksandrovich Doroshenko