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).
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Patent number: 12047600Abstract: A method for setting the motion vector list and the apparatus using the same may include determining the presence of a first motion vector or a second motion vector by a sequential determination process in a first spatial candidate prediction group; and setting the first motion vector or the second motion vector produced through the sequential determination process as the candidate prediction motion vector. Thus, the encoding/decoding time and the complexity can be reduced by restricting the scaling number in a process for scanning the candidate prediction motion vector.Type: GrantFiled: July 14, 2023Date of Patent: July 23, 2024Assignee: LG Electronics Inc.Inventors: Seung Wook Park, Jae Hyun Lim, Jung Sun Kim, Joon Young Park, Young Hee Choi, Byeong Moon Jeon, Yong Joon Jeon
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Patent number: 12013986Abstract: 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: GrantFiled: June 13, 2022Date of Patent: June 18, 2024Assignee: Purdue Research FoundationInventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
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Publication number: 20230044664Abstract: 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: ApplicationFiled: June 13, 2022Publication date: February 9, 2023Inventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
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Patent number: 11360570Abstract: 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: GrantFiled: November 30, 2020Date of Patent: June 14, 2022Assignee: Purdue Research FoundationInventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
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Publication number: 20210081055Abstract: 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: ApplicationFiled: November 30, 2020Publication date: March 18, 2021Inventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
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Patent number: 10852840Abstract: 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: GrantFiled: December 9, 2019Date of Patent: December 1, 2020Assignee: Purdue Research FoundationInventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
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Publication number: 20200225761Abstract: 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: ApplicationFiled: December 9, 2019Publication date: July 16, 2020Inventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
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Patent number: 10503270Abstract: 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: GrantFiled: June 10, 2019Date of Patent: December 10, 2019Assignee: Purdue Research FoundationInventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
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Publication number: 20190310716Abstract: 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: ApplicationFiled: June 10, 2019Publication date: October 10, 2019Inventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
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Patent number: 10318008Abstract: 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: GrantFiled: December 15, 2016Date of Patent: June 11, 2019Assignee: Purdue Research FoundationInventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani
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Publication number: 20170168586Abstract: 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: ApplicationFiled: December 15, 2016Publication date: June 15, 2017Inventors: Ayan Sinha, Chiho Choi, Joon Hee Choi, Karthik Ramani