Patents by Inventor Angus Kong

Angus Kong 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).

  • Patent number: 12354355
    Abstract: Aspects of the present disclosure involve a system comprising a medium storing a program and method for machine-learning based selection of a representative video frame. The program and method provide for receiving a set of video frames; determining a first subset of frames by removing frames outside of an image quality threshold; determining a second subset by removing frames outside of an image stillness threshold; computing feature data for each frame in the second subset; providing, for each frame in the second subset, the feature data to a machine learning model (MLM), the MLM being configured to output a score for each frame in the second subset of frames based on the feature data, the MLM having been trained with a first set of images labeled based on aesthetics, and with a second set of images labeled based on image quality; and selecting a frame based on output scores.
    Type: Grant
    Filed: May 2, 2024
    Date of Patent: July 8, 2025
    Assignee: Snap Inc.
    Inventors: Kavya Venkata Kota Kopparapu, Benjamin Dodson, Francesc Xavier Drudis Rius, Angus Kong, Richard Leider, Jian Ren, Sergey Tulyakov, Jiayao Yu
  • Publication number: 20240282110
    Abstract: Aspects of the present disclosure involve a system comprising a medium storing a program and method for machine-learning based selection of a representative video frame. The program and method provide for receiving a set of video frames; determining a first subset of frames by removing frames outside of an image quality threshold; determining a second subset by removing frames outside of an image stillness threshold; computing feature data for each frame in the second subset; providing, for each frame in the second subset, the feature data to a machine learning model (MLM), the MLM being configured to output a score for each frame in the second subset of frames based on the feature data, the MLM having been trained with a first set of images labeled based on aesthetics, and with a second set of images labeled based on image quality; and selecting a frame based on output scores.
    Type: Application
    Filed: May 2, 2024
    Publication date: August 22, 2024
    Inventors: Kavya Venkata Kota Kopparapu, Benjamin Dodson, Francesc Xavier Drudis Rius, Angus Kong, Richard Leider, Jien Ren, Sergey Tulyakov, Jiayao Yu
  • Patent number: 12008811
    Abstract: Aspects of the present disclosure involve a system comprising a medium storing a program and method for machine-learning based selection of a representative video frame. The program and method provide for receiving a set of video frames; determining a first subset of frames by removing frames outside of an image quality threshold; determining a second subset by removing frames outside of an image stillness threshold; computing feature data for each frame in the second subset; providing, for each frame in the second subset, the feature data to a machine learning model (MLM), the MLM being configured to output a score for each frame in the second subset of frames based on the feature data, the MLM having been trained with a first set of images labeled based on aesthetics, and with a second set of images labeled based on image quality; and selecting a frame based on output scores.
    Type: Grant
    Filed: December 14, 2021
    Date of Patent: June 11, 2024
    Assignee: SNAP INC.
    Inventors: Kavya Venkata Kota Kopparapu, Benjamin Dodson, Francesc Xavier Drudis Rius, Angus Kong, Richard Leider, Jian Ren, Sergey Tulyakov, Jiayao Yu
  • Publication number: 20220207875
    Abstract: Aspects of the present disclosure involve a system comprising a medium storing a program and method for machine-learning based selection of a representative video frame. The program and method provide for receiving a set of video frames; determining a first subset of frames by removing frames outside of an image quality threshold; determining a second subset by removing frames outside of an image stillness threshold; computing feature data for each frame in the second subset; providing, for each frame in the second subset, the feature data to a machine learning model (MLM), the MLM being configured to output a score for each frame in the second subset of frames based on the feature data, the MLM having been trained with a first set of images labeled based on aesthetics, and with a second set of images labeled based on image quality; and selecting a frame based on output scores.
    Type: Application
    Filed: December 14, 2021
    Publication date: June 30, 2022
    Inventors: Kavya Venkata Kota Kopparapu, Benjamin Dodson, Francesc Xavier Drudis Rius, Angus Kong, Richard Leider, Jian Ren, Sergey Tulyakov, Jiayao Yu