Patents by Inventor Christopher PRAMERDORFER

Christopher PRAMERDORFER 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).

  • Method for determining a type and a state of an object of interest
    Patent number: 11790642
    Abstract: The disclosed subject matter relates to a method for determining a type and a state of an object of interest, comprising: generating a depth map of a scene by means of a depth sensor, the scene containing the object of interest and an occlusion object lying between the depth sensor and the object of interest; computing three 2D occupancy views, each in a different viewing direction, and three 2D occlusion views; feeding each of said occupancy and occlusion views into a different input of a trained convolutional neural network; receiving both a class and a bounding box of the object of interest from the convolutional neural network; and determining the type of the object of interest and the state of the object of interest. The disclosed subject matter further relates to a system for carrying out said method.
    Type: Grant
    Filed: April 5, 2019
    Date of Patent: October 17, 2023
    Assignees: CogVis Software und Consulting GmbH, Toyota Motor Europe NV/SA
    Inventors: Martin Kampel, Christopher Pramerdorfer, Rainer Planinc, Michael Brandstoetter, Mark Van Loock
  • METHOD FOR DETERMINING A TYPE AND A STATE OF AN OBJECT OF INTEREST
    Publication number: 20210142091
    Abstract: The disclosed subject matter relates to a method for determining a type and a state of an object of interest, comprising: generating a depth map of a scene by means of a depth sensor, the scene containing the object of interest and an occlusion object lying between the depth sensor and the object of interest; computing three 2D occupancy views, each in a different viewing direction, and three 2D occlusion views; feeding each of said occupancy and occlusion views into a different input of a trained convolutional neural network; receiving both a class and a bounding box of the object of interest from the convolutional neural network; and determining the type of the object of interest and the state of the object of interest. The disclosed subject matter further relates to a system for carrying out said method.
    Type: Application
    Filed: April 5, 2019
    Publication date: May 13, 2021
    Applicants: CogVis Software und Consulting GmbH, Toyota Motor Europe NV/SA
    Inventors: Martin KAMPEL, Christopher PRAMERDORFER, Rainer PLANINC, Michael BRANDSTOETTER, Mark VAN LOOCK