HP Labs IndiaResearch - Pen Based Interfaces and Handwriting Recognition project
|Generic Gesture and Character Recognition|
Our research explores generic features and classification algorithms for recognition of isolated gestures and characters. With gestures, a key problem is to learn models from very small numbers of training samples, and personalize them for the specific user using implicit feedback. Active-DTW is an example of a classification method that we have developed that combines the best of Active Shape Models and Dynamic Time Warping for matching shapes.
We have also been active in online recognition of characters and words in Indic languages and scripts. A supporting activity is the creation of linguistic resources to support such research. More information about this thread below:
|Lipi Toolkit (LipiTk)|
An offshoot of our work in handwriting
recognition is the open source Lipi Toolkit, a collection
of tools and algorithms for building handwriting recognition
engines. The toolkit is being used internally as well, for
example: for gesture recognition for the Gesture Keyboard,
a text input solution for Indic languages.
Our research in this area focuses on:
Graphical tools for handwriting
Scripts and graphical tools for
the analysis of recognition accuracy and errors
Algorithms for handwritten shape
recognition, build scripts for building engines, and
support for UNIPEN 1.0 and a standard shape recognition
The toolkit focuses on:
- supporting collaborative HWR R&D in academic and industrial settings, tools for user interface research.
- supporting commercial HWR development.
Promotion of standard ink representations
Promotion of sharing & reuse
of tools, algorithms, code and handwriting datasets.
Promotion of product and solution
More information on Lipi Toolkit is available at: lipitk.sourceforge.net
Collaborative Inking refers to the investigation of the use of digital ink (pen input) to enable simple kinds of multi-party collaboration using handwritten annotations. This leverages our involvement with W3C InkML, a device and platform independent representation for digital ink.
The core research problems in this area have to do with the design of the interaction, secure and efficient streaming of ink, and synchronization with other modalities such as voice and images, across multiple client devices which may vary widely in capabilities
InkML is an XML data format and a draft W3C standard for platform and device-neutral representation of digital ink data that is input with an electronic pen or stylus. InkML Toolkit (InkMLTk) is targeted at providing a suite of tools for working with InkML documents.
The open source toolkit from HP Labs India includes InkML processor libraries implementing the W3C InkML specification and different kind of tools such as Converters (to and from other ink and image formats), InkML viewers including browser plug-ins, and InkML applications such as a graphical editor.
More information on InkML Toolkit is available at: inkmltk.sourceforge.net
Coffei (Common Forms Framework for Electronic Ink) developed by HP Labs India allows handwriting captured as digital ink on paper forms to be directly converted into machine-readable format using ICR (Intelligent Character Recognition) and integrated into databases and backend systems.
Coffei supports a number of ink-enabled devices ranging from stylus-enabled PDAs and TabletPCs to Anoto pens and electronic clipboards. The use of W3C InkML for representing digital ink ensures interoperability across devices and platforms. Coffei also provides rich support for managing users, forms, devices, and web services for forms processing.
This page was last updated on March 12, 2010
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