Patents by Inventor Joon Hee Choi

Joon Hee Choi 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: 20230044664
    Abstract: A method for hand pose identification in an automated system includes providing map data of a hand of a user to a first neural network trained to classify features corresponding to a joint angle of a wrist in the hand to generate a first plurality of activation features and performing a first search in a predetermined plurality of activation features stored in a database in the memory to identify a first plurality of hand pose parameters for the wrist associated with predetermined activation features in the database that are nearest neighbors to the first plurality of activation features. The method further includes generating a hand pose model corresponding to the hand of the user based on the first plurality of hand pose parameters and performing an operation in the automated system in response to input from the user based on the hand pose model.
    Type: Application
    Filed: June 13, 2022
    Publication date: February 9, 2023
    Inventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
  • Patent number: 11360570
    Abstract: A method for hand pose identification in an automated system includes providing depth map data of a hand of a user to a first neural network trained to classify features corresponding to a joint angle of a wrist in the hand to generate a first plurality of activation features and performing a first search in a predetermined plurality of activation features stored in a database in the memory to identify a first plurality of hand pose parameters for the wrist associated with predetermined activation features in the database that are nearest neighbors to the first plurality of activation features. The method further includes generating a hand pose model corresponding to the hand of the user based on the first plurality of hand pose parameters and performing an operation in the automated system in response to input from the user based on the hand pose model.
    Type: Grant
    Filed: November 30, 2020
    Date of Patent: June 14, 2022
    Assignee: Purdue Research Foundation
    Inventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
  • Publication number: 20210081055
    Abstract: A method for hand pose identification in an automated system includes providing depth map data of a hand of a user to a first neural network trained to classify features corresponding to a joint angle of a wrist in the hand to generate a first plurality of activation features and performing a first search in a predetermined plurality of activation features stored in a database in the memory to identify a first plurality of hand pose parameters for the wrist associated with predetermined activation features in the database that are nearest neighbors to the first plurality of activation features. The method further includes generating a hand pose model corresponding to the hand of the user based on the first plurality of hand pose parameters and performing an operation in the automated system in response to input from the user based on the hand pose model.
    Type: Application
    Filed: November 30, 2020
    Publication date: March 18, 2021
    Inventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
  • Patent number: 10852840
    Abstract: A method for hand pose identification in an automated system includes providing depth map data of a hand of a user to a first neural network trained to classify features corresponding to a joint angle of a wrist in the hand to generate a first plurality of activation features and performing a first search in a predetermined plurality of activation features stored in a database in the memory to identify a first plurality of hand pose parameters for the wrist associated with predetermined activation features in the database that are nearest neighbors to the first plurality of activation features. The method further includes generating a hand pose model corresponding to the hand of the user based on the first plurality of hand pose parameters and performing an operation in the automated system in response to input from the user based on the hand pose model.
    Type: Grant
    Filed: December 9, 2019
    Date of Patent: December 1, 2020
    Assignee: Purdue Research Foundation
    Inventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
  • Publication number: 20200225761
    Abstract: A method for hand pose identification in an automated system includes providing depth map data of a hand of a user to a first neural network trained to classify features corresponding to a joint angle of a wrist in the hand to generate a first plurality of activation features and performing a first search in a predetermined plurality of activation features stored in a database in the memory to identify a first plurality of hand pose parameters for the wrist associated with predetermined activation features in the database that are nearest neighbors to the first plurality of activation features. The method further includes generating a hand pose model corresponding to the hand of the user based on the first plurality of hand pose parameters and performing an operation in the automated system in response to input from the user based on the hand pose model.
    Type: Application
    Filed: December 9, 2019
    Publication date: July 16, 2020
    Inventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
  • Patent number: 10503270
    Abstract: A method for training a hierarchy of trained neural networks for hand pose detection includes training a first neural network to generate a first plurality of activation features that classify an input depth map data corresponding to a hand based on a wrist angle of the hand, the training using a plurality of depth maps of a hand with predetermined wrist angles as inputs to the first neural network during the training, and storing the first neural network in a memory after the training for use in classifying an additional depth map corresponding to a hand based on an angle of a wrist of the hand in the additional depth map.
    Type: Grant
    Filed: June 10, 2019
    Date of Patent: December 10, 2019
    Assignee: Purdue Research Foundation
    Inventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
  • Publication number: 20190310716
    Abstract: A method for hand pose identification in an automated system includes providing depth map data of a hand of a user to a first neural network trained to classify features corresponding to a joint angle of a wrist in the hand to generate a first plurality of activation features and performing a first search in a predetermined plurality of activation features stored in a database in the memory to identify a first plurality of hand pose parameters for the wrist associated with predetermined activation features in the database that are nearest neighbors to the first plurality of activation features. The method further includes generating a hand pose model corresponding to the hand of the user based on the first plurality of hand pose parameters and performing an operation in the automated system in response to input from the user based on the hand pose model.
    Type: Application
    Filed: June 10, 2019
    Publication date: October 10, 2019
    Inventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
  • Patent number: 10318008
    Abstract: A method for hand pose identification in an automated system includes providing depth map data of a hand of a user to a first neural network trained to classify features corresponding to a joint angle of a wrist in the hand to generate a first plurality of activation features and performing a first search in a predetermined plurality of activation features stored in a database in the memory to identify a first plurality of hand pose parameters for the wrist associated with predetermined activation features in the database that are nearest neighbors to the first plurality of activation features. The method further includes generating a hand pose model corresponding to the hand of the user based on the first plurality of hand pose parameters and performing an operation in the automated system in response to input from the user based on the hand pose model.
    Type: Grant
    Filed: December 15, 2016
    Date of Patent: June 11, 2019
    Assignee: Purdue Research Foundation
    Inventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
  • Publication number: 20170168586
    Abstract: A method for hand pose identification in an automated system includes providing depth map data of a hand of a user to a first neural network trained to classify features corresponding to a joint angle of a wrist in the hand to generate a first plurality of activation features and performing a first search in a predetermined plurality of activation features stored in a database in the memory to identify a first plurality of hand pose parameters for the wrist associated with predetermined activation features in the database that are nearest neighbors to the first plurality of activation features. The method further includes generating a hand pose model corresponding to the hand of the user based on the first plurality of hand pose parameters and performing an operation in the automated system in response to input from the user based on the hand pose model.
    Type: Application
    Filed: December 15, 2016
    Publication date: June 15, 2017
    Inventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani