Patents by Inventor Xavier Alameda-Pineda

Xavier Alameda-Pineda 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).

  • Self-adaptive matrix completion for heart rate estimation from face videos under realistic conditions
    Patent number: 10335045
    Abstract: Recent studies in computer vision have shown that, while practically invisible to a human observer, skin color changes due to blood flow can be captured on face videos and, surprisingly, be used to estimate the heart rate (HR). While considerable progress has been made in the last few years, still many issues remain open. In particular, state-of-the-art approaches are not robust enough to operate in natural conditions (e.g. in case of spontaneous movements, facial expressions, or illumination changes). Opposite to previous approaches that estimate the HR by processing all the skin pixels inside a fixed region of interest, we introduce a strategy to dynamically select face regions useful for robust HR estimation. The present approach, inspired by recent advances on matrix completion theory, allows us to predict the HR while simultaneously discover the best regions of the face to be used for estimation.
    Type: Grant
    Filed: June 23, 2017
    Date of Patent: July 2, 2019
    Assignees: Universita degli Studi Di Trento, Fondazione Bruno Kessler, The Research Foundation for the State University of New York, University of Pittsburgh of the Commonwealth of Higher Education
    Inventors: Niculae Sebe, Xavier Alameda-Pineda, Sergey Tulyakov, Elisa Ricci, Lijun Yin, Jeffrey F. Cohn
  • SELF-ADAPTIVE MATRIX COMPLETION FOR HEART RATE ESTIMATION FROM FACE VIDEOS UNDER REALISTIC CONDITIONS
    Publication number: 20170367590
    Abstract: Recent studies in computer vision have shown that, while practically invisible to a human observer, skin color changes due to blood flow can be captured on face videos and, surprisingly, be used to estimate the heart rate (HR). While considerable progress has been made in the last few years, still many issues remain open. In particular, state-of-the-art approaches are not robust enough to operate in natural conditions (e.g. in case of spontaneous movements, facial expressions, or illumination changes). Opposite to previous approaches that estimate the HR by processing all the skin pixels inside a fixed region of interest, we introduce a strategy to dynamically select face regions useful for robust HR estimation. The present approach, inspired by recent advances on matrix completion theory, allows us to predict the HR while simultaneously discover the best regions of the face to be used for estimation.
    Type: Application
    Filed: June 23, 2017
    Publication date: December 28, 2017
    Inventors: Niculae Sebe, Xavier Alameda-Pineda, Sergey Tulyakov, Elisa Ricci, Lijun Yin, Jeffrey F. Cohn