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.

A handwriting input device, in response to a handwriting operation that moves an object on an input surface with the object contacting the input surface, inputs information corresponding to the path of the contact position of the object on the input surface. The handwriting input device includes a sensor part and a determining part. The sensor part detects the contact position of the object on the input surface and the presence or absence of the object within a predetermined operation space adjacent to the input surface. The determining part determines the start and the end of the handwriting operation based on the detection result of the sensor part. The determining part determines the continuance of the handwriting operation in response to detecting the presence of the object within the operation space by the sensor part after determining the start of the handwriting operation.

A digital ink processing system, method, and program are provided that are capable of presenting, to a user, useful and highly relevant information as a search result when a search is performed using digital ink. A processor included in a tablet enables a pointing operation of an electronic pen relative to a stroke or strokes. The processor, after enabling the pointing operation of the electronic pen, performs a search for content related to a semantic attribute of the stroke or strokes pointed at, or requests an external server to perform the search. The processor performs control so as to display the related content retrieved by the search on a display with the stroke or strokes.

A communication system captures writing surface content in a physical space for transmittal to remote client devices participating in a communication session. During a communication session with one or more remote client devices, a communication system captures image data and depth data describing objects in a physical space of the communication system. Based on the captured data, the communication system identifies a writing surface in the physical space and captures content on the writing surface. The communication system may also identify objects occluding content on the writing surface based on the captured data and may modify image data to make an object occluding the content at least partially transparent. The communication system transmits the content to at least one of the remote client devices participating in the communication session.

A method of outputting digital ink data includes: detecting one or more pieces of stroke data; judging whether the one or more pieces of stroke data form a complete unit of semantics; in a case that the one or more pieces of the stroke data form the complete unit of semantics, aggregating the one or more pieces of stroke data into one message; and outputting the aggregated one or more pieces of stroke data together in the one message.

Preserving ink effects in ink-to-text are described. A method of preserving styles and ink effects in ink-to-text can include receiving ink strokes and displaying the ink strokes on a canvas interface, each ink stroke comprising ink parameters such as pressure, ink color, and ink effect. In response to receiving a command to convert one or more ink strokes to text, the method can further include identifying text comprising characters and words from the one or more ink strokes; generating an appropriate coloring or style for each character or word based on the ink parameters associated with corresponding ink strokes, the appropriate coloring or style being generated based on a mapping between ink parameters and text parameters; applying the appropriate coloring or style to the text; and displaying the text on the canvas interface.

Vector format based computer graphics tools have become very powerful tools allowing artists, designers etc. to mimic many artistic styles, exploit automated techniques, etc. and across different simulated physical media and digital media. However, hand-drawing and sketching in vector format graphics is unnatural and a user's strokes rendered by software are generally unnatural and appear artificial. In contrast to today's hand-drawing and sketching which requires significant training of and understanding by the user of complex vector graphics methods embodiments of the invention lower the barrier to accessing computer graphics applications for users in respect of making hand-drawing or sketching easier to perform. Accordingly, the inventors have established a direct vector-based hand-drawing/sketching entry format supporting any input methodology.

A data processing system for performing a semantic analysis of digital ink stroke data implements obtaining the digital ink stroke data representing handwritten text, drawings, or both; analyzing the digital ink stroke data to extract path signature feature information from the digital ink stroke data; analyzing the path signature feature information using a convolutional neural network (CNN) trained to perform a pixel-level sematic analysis of the digital ink stroke data and to output a pixel segmentation map with semantic prediction information for each pixel of digital ink stroke data; analyzing the pixel segmentation map to generate stroke-level semantic information using a pixel-to-stroke conversion model; and processing the digital ink stroke data based on the stroke-level semantic information.

A handwriting recognition method is provided, which includes: obtaining handwritten original trajectory data in real-time; compressing the handwritten original trajectory data, to obtain compressed handwritten trajectory data; and inputting the compressed handwritten trajectory data into a compressed handwriting recognition model for recognition, to obtain a text recognition result corresponding to the handwritten original trajectory data. A handwriting recognition model is obtained by training with handwritten trajectory data of each piece of training data in a training data set, and the compressed handwriting recognition model is obtained by performing model compression on the handwriting recognition model. The handwriting recognition method can address the problem in the related art that the handwriting recognition accuracy is low caused by incorrect segmentation, thereby effectively improving the handwriting recognition accuracy.

A computer-implemented method for automatically analyzing handwritten text to determine a mismatch between a purported writer and an actual writer is disclosed. The method comprises receiving two samples of digitized handwriting each allegedly created by one individual and received and entered into a digital system by another. The method further comprises performing a series of feature extractions to convert the samples into two vectors of extracted features; automatically clustering a set of vectors such that the first vector and the second vector are assigned to the same cluster among multiple clusters, based on vector similarity; and automatically determining that a same individual being associated with both the first and second samples indicates a heightened probability that the individual fraudulently created both samples. Finally, the method comprises automatically transmitting a message to flag additional samples of digitized handwriting entered into a digital system as possibly fraudulent.