a wordcloud of handwriting recognition terms.

CUBS projects are funded by industry and government agencies. Federal sponsors include the Army Research Labs, the Central Intelligence Agency, the Defense Intelligence Agency, and the National Science Foundation. Industry sponsors include BBN Raytheon, Google, HP, IBM, and Lockheed Martin.

  • Multilingual OCR
    Our objective is to automatically recognize handwritten and mixed-type documents in multiple languages. Our current focus is on pre-processing of documents and development of novel features for handwriting recognition.
  • Historical Documents
    We are exploring the development of computational methodologies and applications that will enable user-friendly digital access to literary and historical document images in Sanskrit.
  • Tablet and PDA Interfaces
    We are investigating a new kind of scientific information interface which involves the use of a touch screen device such as a tablet, supporting sketching and handwriting input to access, annotate, store and retrieve research material. Personal research materials can therefore be organized and shared selectively in a reliable social networking environment by academic researchers.
  • Medical Informatics
    Emergency Medical Systems (EMS) agencies, as first responders in medical emergency scenarios, are uniquely positioned to provide valuable data for surveillance and early warning systems.
  • Web Security
    We are developing new technologies to beat the spambots by exploiting the difficulty that computers have with recognizing joined-up handwriting. The hope is that switching from text-based verification systems to systems that use computer-generated handwriting will make many web services more secure.
  • Writer Accent
    We are exploring two hypotheses with respect to analysis of an individual’s handwriting: (i) analogous to speech, accent is a trait that is also present in handwriting and can potentially be used as a novel soft biometric, (ii) an individual’s handwriting is a mixture of writing style influences (right to left versus left to right, short strokes with rapid pen lifts, curves, etc.) and can be decomposed into the constituents.
  • Face and Facial Expressions
    We are creating a new composite biometric that includes the static face appearance features as well as the behavioral expression features that will, in remote authentication applications, verify the humanness, liveness, and the identity of a user in a single interaction.
  • Cancelable Biometrics
    Our focus is on Integrating Privacy Preserving Biometric Templates and Efficient Indexing Methods. While people are usually willing to submit their biometric information to government agencies, they are less likely to do so for commercial companies without a guarantee of privacy protection.