Patents by Inventor Juan Carlos Niebles Duque

Juan Carlos Niebles Duque 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).

  • Publication number: 20210295093
    Abstract: A method for scene perception using video captioning based on a spatio-temporal graph model is described. The method includes decomposing the spatio-temporal graph model of a scene in input video into a spatial graph and a temporal graph. The method also includes modeling a two branch framework having an object branch and a scene branch according to the spatial graph and the temporal graph to learn object interactions between the object branch and the scene branch. The method further includes transferring the learned object interactions from the object branch to the scene branch as privileged information. The method also includes captioning the scene by aligning language logits from the object branch and the scene branch according to the learned object interactions.
    Type: Application
    Filed: March 23, 2020
    Publication date: September 23, 2021
    Applicants: TOYOTA RESEARCH INSTITUTE, INC., THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY
    Inventors: Boxiao PAN, Haoye CAI, De-An HUANG, Kuan-Hui LEE, Adrien David GAIDON, Ehsan ADELI-MOSABBEB, Juan Carlos NIEBLES DUQUE
  • Patent number: 11074438
    Abstract: A method for predicting spatial positions of several key points on a human body in the near future in an egocentric setting is described. The method includes generating a frame-level supervision for human poses. The method also includes suppressing noise and filling missing joints of the human body using a pose completion module. The method further includes splitting the poses into a global stream and a local stream. Furthermore, the method includes combining the global stream and the local stream to forecast future human locomotion.
    Type: Grant
    Filed: October 1, 2019
    Date of Patent: July 27, 2021
    Assignees: TOYOTA RESEARCH INSTITUTE, INC., THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY
    Inventors: Karttikeya Mangalam, Ehsan Adeli-Mosabbeb, Kuan-Hui Lee, Adrien Gaidon, Juan Carlos Niebles Duque
  • Publication number: 20210097266
    Abstract: A method for predicting spatial positions of several key points on a human body in the near future in an egocentric setting is described. The method includes generating a frame-level supervision for human poses. The method also includes suppressing noise and filling missing joints of the human body using a pose completion module. The method further includes splitting the poses into a global stream and a local stream. Furthermore, the method includes combining the global stream and the local stream to forecast future human locomotion.
    Type: Application
    Filed: October 1, 2019
    Publication date: April 1, 2021
    Applicants: TOYOTA RESEARCH INSTITUTE, INC., THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY
    Inventors: Karttikeya MANGALAM, Ehsan ADELI-MOSABBEB, Kuan-Hui LEE, Adrien GAIDON, Juan Carlos NIEBLES DUQUE
  • Patent number: 10210462
    Abstract: A demographics analysis trains classifier models for predicting demographic attribute values of videos and users not already having known demographics. In one embodiment, the demographics analysis system trains classifier models for predicting demographics of videos using video features such as demographics of video uploaders, textual metadata, and/or audiovisual content of videos. In one embodiment, the demographics analysis system trains classifier models for predicting demographics of users (e.g., anonymous users) using user features based on prior video viewing periods of users. For example, viewing-period based user features can include individual viewing period statistics such as total videos viewed. Further, the viewing-period based features can include distributions of values over the viewing period, such as distributions in demographic attribute values of video uploaders, and/or distributions of viewings over hours of the day, days of the week, and the like.
    Type: Grant
    Filed: November 24, 2014
    Date of Patent: February 19, 2019
    Assignee: Google LLC
    Inventors: Juan Carlos Niebles Duque, Hrishikesh Aradhye, Luciano Sbaiz, Jay Yagnik, Reto Strobl
  • Publication number: 20150081604
    Abstract: A demographics analysis trains classifier models for predicting demographic attribute values of videos and users not already having known demographics. In one embodiment, the demographics analysis system trains classifier models for predicting demographics of videos using video features such as demographics of video uploaders, textual metadata, and/or audiovisual content of videos. In one embodiment, the demographics analysis system trains classifier models for predicting demographics of users (e.g., anonymous users) using user features based on prior video viewing periods of users. For example, viewing-period based user features can include individual viewing period statistics such as total videos viewed. Further, the viewing-period based features can include distributions of values over the viewing period, such as distributions in demographic attribute values of video uploaders, and/or distributions of viewings over hours of the day, days of the week, and the like.
    Type: Application
    Filed: November 24, 2014
    Publication date: March 19, 2015
    Inventors: Juan Carlos Niebles Duque, Hrishikesh Aradhye, Luciano Sbaiz, Jay Yagnik, Reto Strobl
  • Patent number: 8924993
    Abstract: A demographics analysis trains classifier models for predicting demographic attribute values of videos and users not already having known demographics. In one embodiment, the demographics analysis system trains classifier models for predicting demographics of videos using video features such as demographics of video uploaders, textual metadata, and/or audiovisual content of videos. In one embodiment, the demographics analysis system trains classifier models for predicting demographics of users (e.g., anonymous users) using user features based on prior video viewing periods of users. For example, viewing-period based user features can include individual viewing period statistics such as total videos viewed. Further, the viewing-period based features can include distributions of values over the viewing period, such as distributions in demographic attribute values of video uploaders, and/or distributions of viewings over hours of the day, days of the week, and the like.
    Type: Grant
    Filed: November 10, 2011
    Date of Patent: December 30, 2014
    Assignee: Google Inc.
    Inventors: Juan Carlos Niebles Duque, Hrishikesh Balkrishna Aradhye, Luciano Sbaiz, Jay N. Yagnik, Reto Strobl