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US Patent 10318008 Method and system for hand pose detection

Patent 10318008 was granted and assigned to Purdue Research Foundation on June, 2019 by the United States Patent and Trademark Office.

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Contents

Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent

Patent attributes

Patent Applicant
Purdue Research Foundation
Purdue Research Foundation
Current Assignee
Purdue Research Foundation
Purdue Research Foundation
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10318008
Date of Patent
June 11, 2019
Patent Application Number
15380002
Date Filed
December 15, 2016
Patent Citations Received
‌
US Patent 12001610 Three-dimensional perceptions in haptic systems
3
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US Patent 11921928 Haptic effects from focused acoustic fields
4
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US Patent 11955109 Driving techniques for phased-array systems
5
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US Patent 12002448 Acoustic transducer structures
6
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US Patent 11531395 Haptic effects from focused acoustic fields
‌
US Patent 10614591 Hand tracking based on articulated distance field
‌
US Patent 11543507 Method and apparatus for producing an acoustic field
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US Patent 11550432 Perceptions in a haptic system
...
Patent Primary Examiner
‌
Laurence J Lee
Patent 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.

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