Patents by Inventor Karthir Prabhakar

Karthir Prabhakar has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Systems and methods for retrieving causal sets of events from unstructured signals
    Patent number: 8909025
    Abstract: A method for providing improved performance in retrieving and classifying causal sets of events from an unstructured signal can comprise applying a temporal-causal analysis to the unstructured signal. The temporal-causal analysis can comprise representing the occurrence times of visual events from an unstructured signal as a set of point processes. An exemplary embodiment can comprise interpreting a set of visual codewords produced by a space-time-dictionary representation of the unstructured video sequence as the set of point processes. A nonparametric estimate of the cross-spectrum between pairs of point processes can be obtained. In an exemplary embodiment, a spectral version of the pairwise test for Granger causality can be applied to the nonparametric estimate to identify patterns of interactions between visual codewords and group them into semantically meaningful independent causal sets.
    Type: Grant
    Filed: March 22, 2012
    Date of Patent: December 9, 2014
    Assignee: Georgia Tech Research Corporation
    Inventors: James M. Rehg, Karthir Prabhakar, Sangmin Oh, Ping Wang, Gregory D. Abowd
  • SYSTEMS AND METHODS FOR RETRIEVING CASUAL SETS OF EVENTS FROM UNSTRUCTURED SIGNALS
    Publication number: 20120301105
    Abstract: A method for providing improved performance in retrieving and classifying causal sets of events from an unstructured signal can comprise applying a temporal-causal analysis to the unstructured signal. The temporal-causal analysis can comprise representing the occurrence times of visual events from an unstructured signal as a set of point processes. An exemplary embodiment can comprise interpreting a set of visual codewords produced by a space-time-dictionary representation of the unstructured video sequence as the set of point processes. A nonparametric estimate of the cross-spectrum between pairs of point processes can be obtained. In an exemplary embodiment, a spectral version of the pairwise test for Granger causality can be applied to the nonparametric estimate to identify patterns of interactions between visual codewords and group them into semantically meaningful independent causal sets.
    Type: Application
    Filed: March 22, 2012
    Publication date: November 29, 2012
    Applicant: Georgia Tech Research Corporation
    Inventors: James M. Rehg, Karthir Prabhakar, Sangmin Oh, Ping Wang, Gregory D. Abowd