Patents by Inventor Michael Menefee

Michael Menefee 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: 11954904
    Abstract: Disclosed are methods, apparatus and systems for real-time gesture recognition. One exemplary method for the real-time identification of a gesture communicated by a subject includes receiving, by a first thread of the one or more multi-threaded processors, a first set of image frames associated with the gesture, the first set of image frames captured during a first time interval, performing, by the first thread, pose estimation on each frame of the first set of image frames including eliminating background information from each frame to obtain one or more areas of interest, storing information representative of the one or more areas of interest in a shared memory accessible to the one or more multi-threaded processors, and performing, by a second thread of the one or more multi-threaded processors, a gesture recognition operation on a second set of image frames associated with the gesture.
    Type: Grant
    Filed: July 6, 2021
    Date of Patent: April 9, 2024
    Assignee: AVODAH, INC.
    Inventors: Trevor Chandler, Dallas Nash, Michael Menefee
  • Patent number: 11928592
    Abstract: Methods, devices and systems for training a pattern recognition system are described. In one example, a method for training a sign language translation system includes generating a three-dimensional (3D) scene that includes a 3D model simulating a gesture that represents a letter, a word, or a phrase in a sign language. The method includes obtaining a value indicative of a total number of training images to be generated, using the value indicative of the total number of training images to determine a plurality of variations of the 3D scene for generating of the training images, applying each of plurality of variations to the 3D scene to produce a plurality of modified 3D scenes, and capturing an image of each of the plurality of modified 3D scenes to form the training images for a neural network of the sign language translation system.
    Type: Grant
    Filed: June 14, 2021
    Date of Patent: March 12, 2024
    Assignee: Avodah, Inc.
    Inventors: Trevor Chandler, Dallas Nash, Michael Menefee
  • Publication number: 20230377376
    Abstract: Methods, apparatus and systems for recognizing sign language movements using multiple input and output modalities. One example method includes capturing a movement associated with the sign language using a set of visual sensing devices, the set of visual sensing devices comprising multiple apertures oriented with respect to the subject to receive optical signals corresponding to the movement from multiple angles, generating digital information corresponding to the movement based on the optical signals from the multiple angles, collecting depth information corresponding to the movement in one or more planes perpendicular to an image plane captured by the set of visual sensing devices, producing a reduced set of digital information by removing at least some of the digital information based on the depth information, generating a composite digital representation by aligning at least a portion of the reduced set of digital information, and recognizing the movement based on the composite digital representation.
    Type: Application
    Filed: January 17, 2023
    Publication date: November 23, 2023
    Inventors: Michael Menefee, Dallas Nash, Trevor Chandler
  • Patent number: 11557152
    Abstract: Methods, apparatus and systems for recognizing sign language movements using multiple input and output modalities. One example method includes capturing a movement associated with the sign language using a set of visual sensing devices, the set of visual sensing devices comprising multiple apertures oriented with respect to the subject to receive optical signals corresponding to the movement from multiple angles, generating digital information corresponding to the movement based on the optical signals from the multiple angles, collecting depth information corresponding to the movement in one or more planes perpendicular to an image plane captured by the set of visual sensing devices, producing a reduced set of digital information by removing at least some of the digital information based on the depth information, generating a composite digital representation by aligning at least a portion of the reduced set of digital information, and recognizing the movement based on the composite digital representation.
    Type: Grant
    Filed: March 22, 2021
    Date of Patent: January 17, 2023
    Assignee: AVODAH, INC.
    Inventors: Michael Menefee, Dallas Nash, Trevor Chandler
  • Patent number: 11270301
    Abstract: A system for combining a payment mechanism with an offer to a consumer is described. The system includes a virtual payment account number generation engine to generate virtual payment account numbers that can be used by a consumer in a payment transaction at a merchant, the virtual payment account number generation service also operable to take a portion of the virtual payment account number and send it as a checkout code to a consumer using the consumer's mobile device, and an offer generation engine used to set rules for an offer to be sent to consumers, create a fund for the offer, and determine individual consumer's eligibility for the offer. The offer is associated with the checkout code such that the offer is processed as part of the payment during the payment transaction using the virtual payment account number.
    Type: Grant
    Filed: June 9, 2014
    Date of Patent: March 8, 2022
    Assignee: ModoPayments, LLC
    Inventors: Gregory W. Harvey, Samuel N. Brown, David S. Sink, Aaron Wilkinson, Michael Menefee, Mark S. Saum, Colm Bergin, Bruce Parker, Ralf Erich Schulz, Jon Buell, Jason Fisher
  • Publication number: 20220036050
    Abstract: Disclosed are methods, apparatus and systems for real-time gesture recognition. One exemplary method for the real-time identification of a gesture communicated by a subject includes receiving, by a first thread of the one or more multi-threaded processors, a first set of image frames associated with the gesture, the first set of image frames captured during a first time interval, performing, by the first thread, pose estimation on each frame of the first set of image frames including eliminating background information from each frame to obtain one or more areas of interest, storing information representative of the one or more areas of interest in a shared memory accessible to the one or more multi-threaded processors, and performing, by a second thread of the one or more multi-threaded processors, a gesture recognition operation on a second set of image frames associated with the gesture.
    Type: Application
    Filed: July 6, 2021
    Publication date: February 3, 2022
    Inventors: Trevor Chandler, Dallas Nash, Michael Menefee
  • Publication number: 20220026992
    Abstract: Disclosed are methods, apparatus and systems for gesture recognition based on neural network processing. One exemplary method for identifying a gesture communicated by a subject includes receiving a plurality of images associated with the gesture, providing the plurality of images to a first 3-dimensional convolutional neural network (3D CNN) and a second 3D CNN, where the first 3D CNN is operable to produce motion information, where the second 3D CNN is operable to produce pose and color information, and where the first 3D CNN is operable to implement an optical flow algorithm to detect the gesture, fusing the motion information and the pose and color information to produce an identification of the gesture, and determining whether the identification corresponds to a singular gesture across the plurality of images using a recurrent neural network that comprises one or more long short-term memory units.
    Type: Application
    Filed: August 9, 2021
    Publication date: January 27, 2022
    Inventors: Trevor Chandler, Dallas Nash, Michael Menefee
  • Publication number: 20220027881
    Abstract: Systems and methods are described for incorporating electronic benefit transfer (EBT) systems into a secure, mobile, and electronic payment processing system. Existing EBT systems capture data regarding a purchase. This record keeping functionality can be harnessed to provide retailers and marketers with data regarding marketing efforts, coupon use, and more. A mobile device can be used to interact with a presence detection system. Coupons or payment information can be received at a mobile device, and payments can be carried out between a mobile device and a points of sale (POS).
    Type: Application
    Filed: October 11, 2021
    Publication date: January 27, 2022
    Applicant: ModoPayments, LLC
    Inventors: Aaron Wilkinson, Gregory W. Harvey, Bruce Parker, Michael Menefee
  • Publication number: 20210374393
    Abstract: Methods, devices and systems for training a pattern recognition system are described. In one example, a method for training a sign language translation system includes generating a three-dimensional (3D) scene that includes a 3D model simulating a gesture that represents a letter, a word, or a phrase in a sign language. The method includes obtaining a value indicative of a total number of training images to be generated, using the value indicative of the total number of training images to determine a plurality of variations of the 3D scene for generating of the training images, applying each of plurality of variations to the 3D scene to produce a plurality of modified 3D scenes, and capturing an image of each of the plurality of modified 3D scenes to form the training images for a neural network of the sign language translation system.
    Type: Application
    Filed: June 14, 2021
    Publication date: December 2, 2021
    Inventors: Trevor Chandler, Dallas Nash, Michael Menefee
  • Patent number: 11144905
    Abstract: Systems and methods are described for incorporating electronic benefit transfer (EBT) systems into a secure, mobile, and electronic payment processing system. Existing EBT systems capture data regarding a purchase. This record keeping functionality can be harnessed to provide retailers and marketers with data regarding marketing efforts, coupon use, and more. A mobile device can be used to interact with a presence detection system. Coupons or payment information can be received at a mobile device, and payments can be carried out between a mobile device and a points of sale (POS).
    Type: Grant
    Filed: December 21, 2016
    Date of Patent: October 12, 2021
    Assignee: ModoPayments, LLC
    Inventors: Aaron Wilkinson, Gregory W. Harvey, Bruce Parker, Michael Menefee
  • Publication number: 20210279454
    Abstract: Methods, apparatus and systems for recognizing sign language movements using multiple input and output modalities. One example method includes capturing a movement associated with the sign language using a set of visual sensing devices, the set of visual sensing devices comprising multiple apertures oriented with respect to the subject to receive optical signals corresponding to the movement from multiple angles, generating digital information corresponding to the movement based on the optical signals from the multiple angles, collecting depth information corresponding to the movement in one or more planes perpendicular to an image plane captured by the set of visual sensing devices, producing a reduced set of digital information by removing at least some of the digital information based on the depth information, generating a composite digital representation by aligning at least a portion of the reduced set of digital information, and recognizing the movement based on the composite digital representation.
    Type: Application
    Filed: March 22, 2021
    Publication date: September 9, 2021
    Inventors: Michael Menefee, Dallas Nash, Trevor Chandler
  • Patent number: 11087488
    Abstract: Disclosed are methods, apparatus and systems for gesture recognition based on neural network processing. One exemplary method for identifying a gesture communicated by a subject includes receiving a plurality of images associated with the gesture, providing the plurality of images to a first 3-dimensional convolutional neural network (3D CNN) and a second 3D CNN, where the first 3D CNN is operable to produce motion information, where the second 3D CNN is operable to produce pose and color information, and where the first 3D CNN is operable to implement an optical flow algorithm to detect the gesture, fusing the motion information and the pose and color information to produce an identification of the gesture, and determining whether the identification corresponds to a singular gesture across the plurality of images using a recurrent neural network that comprises one or more long short-term memory units.
    Type: Grant
    Filed: May 23, 2019
    Date of Patent: August 10, 2021
    Assignee: AVODAH, INC.
    Inventors: Trevor Chandler, Dallas Nash, Michael Menefee
  • Patent number: 11055521
    Abstract: Disclosed are methods, apparatus and systems for real-time gesture recognition. One exemplary method for the real-time identification of a gesture communicated by a subject includes receiving, by a first thread of the one or more multi-threaded processors, a first set of image frames associated with the gesture, the first set of image frames captured during a first time interval, performing, by the first thread, pose estimation on each frame of the first set of image frames including eliminating background information from each frame to obtain one or more areas of interest, storing information representative of the one or more areas of interest in a shared memory accessible to the one or more multi-threaded processors, and performing, by a second thread of the one or more multi-threaded processors, a gesture recognition operation on a second set of image frames associated with the gesture.
    Type: Grant
    Filed: December 30, 2019
    Date of Patent: July 6, 2021
    Assignee: AVODAH, INC.
    Inventors: Trevor Chandler, Dallas Nash, Michael Menefee
  • Patent number: 11036973
    Abstract: Methods, devices and systems for training a pattern recognition system are described. In one example, a method for training a sign language translation system includes generating a three-dimensional (3D) scene that includes a 3D model simulating a gesture that represents a letter, a word, or a phrase in a sign language. The method includes obtaining a value indicative of a total number of training images to be generated, using the value indicative of the total number of training images to determine a plurality of variations of the 3D scene for generating of the training images, applying each of plurality of variations to the 3D scene to produce a plurality of modified 3D scenes, and capturing an image of each of the plurality of modified 3D scenes to form the training images for a neural network of the sign language translation system.
    Type: Grant
    Filed: May 13, 2019
    Date of Patent: June 15, 2021
    Assignee: AVODAH, INC.
    Inventors: Trevor Chandler, Dallas Nash, Michael Menefee
  • Patent number: 10956725
    Abstract: Methods, apparatus and systems for recognizing sign language movements using multiple input and output modalities. One example method includes capturing a movement associated with the sign language using a set of visual sensing devices, the set of visual sensing devices comprising multiple apertures oriented with respect to the subject to receive optical signals corresponding to the movement from multiple angles, generating digital information corresponding to the movement based on the optical signals from the multiple angles, collecting depth information corresponding to the movement in one or more planes perpendicular to an image plane captured by the set of visual sensing devices, producing a reduced set of digital information by removing at least some of the digital information based on the depth information, generating a composite digital representation by aligning at least a portion of the reduced set of digital information, and recognizing the movement based on the composite digital representation.
    Type: Grant
    Filed: November 25, 2019
    Date of Patent: March 23, 2021
    Assignee: AVODAH, INC.
    Inventors: Michael Menefee, Dallas Nash, Trevor Chandler
  • Publication number: 20200387697
    Abstract: Disclosed are methods, apparatus and systems for real-time gesture recognition. One exemplary method for the real-time identification of a gesture communicated by a subject includes receiving, by a first thread of the one or more multi-threaded processors, a first set of image frames associated with the gesture, the first set of image frames captured during a first time interval, performing, by the first thread, pose estimation on each frame of the first set of image frames including eliminating background information from each frame to obtain one or more areas of interest, storing information representative of the one or more areas of interest in a shared memory accessible to the one or more multi-threaded processors, and performing, by a second thread of the one or more multi-threaded processors, a gesture recognition operation on a second set of image frames associated with the gesture.
    Type: Application
    Filed: December 30, 2019
    Publication date: December 10, 2020
    Inventors: Trevor Chandler, Dallas Nash, Michael Menefee
  • Publication number: 20200126250
    Abstract: Disclosed are methods, apparatus and systems for gesture recognition based on neural network processing. One exemplary method for identifying a gesture communicated by a subject includes receiving a plurality of images associated with the gesture, providing the plurality of images to a first 3-dimensional convolutional neural network (3D CNN) and a second 3D CNN, where the first 3D CNN is operable to produce motion information, where the second 3D CNN is operable to produce pose and color information, and where the first 3D CNN is operable to implement an optical flow algorithm to detect the gesture, fusing the motion information and the pose and color information to produce an identification of the gesture, and determining whether the identification corresponds to a singular gesture across the plurality of images using a recurrent neural network that comprises one or more long short-term memory units.
    Type: Application
    Filed: May 23, 2019
    Publication date: April 23, 2020
    Inventors: Trevor Chandler, Dallas Nash, Michael Menefee
  • Publication number: 20200104582
    Abstract: Methods, apparatus and systems for recognizing sign language movements using multiple input and output modalities. One example method includes capturing a movement associated with the sign language using a set of visual sensing devices, the set of visual sensing devices comprising multiple apertures oriented with respect to the subject to receive optical signals corresponding to the movement from multiple angles, generating digital information corresponding to the movement based on the optical signals from the multiple angles, collecting depth information corresponding to the movement in one or more planes perpendicular to an image plane captured by the set of visual sensing devices, producing a reduced set of digital information by removing at least some of the digital information based on the depth information, generating a composite digital representation by aligning at least a portion of the reduced set of digital information, and recognizing the movement based on the composite digital representation.
    Type: Application
    Filed: November 25, 2019
    Publication date: April 2, 2020
    Inventors: Michael Menefee, Dallas Nash, Trevor Chandler
  • Patent number: D912139
    Type: Grant
    Filed: January 28, 2019
    Date of Patent: March 2, 2021
    Assignee: AVODAH, INC.
    Inventors: Michael Menefee, Dallas Nash, Trevor Chandler
  • Patent number: D976320
    Type: Grant
    Filed: March 1, 2021
    Date of Patent: January 24, 2023
    Assignee: AVODAH, INC.
    Inventors: Michael Menefee, Dallas Nash, Trevor Chandler